further research suggestions

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

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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.

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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• How to Write a Discussion Section | Tips & Examples

How to Write a Discussion Section | Tips & Examples

Published on August 21, 2022 by Shona McCombes . Revised on July 18, 2023.

The discussion section is where you delve into the meaning, importance, and relevance of your results .

It should focus on explaining and evaluating what you found, showing how it relates to your literature review and paper or dissertation topic , and making an argument in support of your overall conclusion. It should not be a second results section.

There are different ways to write this section, but you can focus your writing around these key elements:

• Summary : A brief recap of your key results
• Interpretations: What do your results mean?
• Implications: Why do your results matter?
• Limitations: What can’t your results tell us?
• Recommendations: Avenues for further studies or analyses

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Table of contents

What not to include in your discussion section, step 1: summarize your key findings, step 2: give your interpretations, step 3: discuss the implications, step 4: acknowledge the limitations, step 5: share your recommendations, discussion section example, other interesting articles, frequently asked questions about discussion sections.

There are a few common mistakes to avoid when writing the discussion section of your paper.

• Don’t introduce new results: You should only discuss the data that you have already reported in your results section .
• Don’t make inflated claims: Avoid overinterpretation and speculation that isn’t directly supported by your data.
• Don’t undermine your research: The discussion of limitations should aim to strengthen your credibility, not emphasize weaknesses or failures.

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Start this section by reiterating your research problem and concisely summarizing your major findings. To speed up the process you can use a summarizer to quickly get an overview of all important findings. Don’t just repeat all the data you have already reported—aim for a clear statement of the overall result that directly answers your main research question . This should be no more than one paragraph.

Many students struggle with the differences between a discussion section and a results section . The crux of the matter is that your results sections should present your results, and your discussion section should subjectively evaluate them. Try not to blend elements of these two sections, in order to keep your paper sharp.

• The results indicate that…
• The study demonstrates a correlation between…
• This analysis supports the theory that…
• The data suggest that…

The meaning of your results may seem obvious to you, but it’s important to spell out their significance for your reader, showing exactly how they answer your research question.

The form of your interpretations will depend on the type of research, but some typical approaches to interpreting the data include:

• Identifying correlations , patterns, and relationships among the data
• Discussing whether the results met your expectations or supported your hypotheses
• Contextualizing your findings within previous research and theory
• Explaining unexpected results and evaluating their significance
• Considering possible alternative explanations and making an argument for your position

You can organize your discussion around key themes, hypotheses, or research questions, following the same structure as your results section. Alternatively, you can also begin by highlighting the most significant or unexpected results.

• In line with the hypothesis…
• Contrary to the hypothesized association…
• The results contradict the claims of Smith (2022) that…
• The results might suggest that x . However, based on the findings of similar studies, a more plausible explanation is y .

As well as giving your own interpretations, make sure to relate your results back to the scholarly work that you surveyed in the literature review . The discussion should show how your findings fit with existing knowledge, what new insights they contribute, and what consequences they have for theory or practice.

Ask yourself these questions:

• Do your results support or challenge existing theories? If they support existing theories, what new information do they contribute? If they challenge existing theories, why do you think that is?
• Are there any practical implications?

Your overall aim is to show the reader exactly what your research has contributed, and why they should care.

• These results build on existing evidence of…
• The results do not fit with the theory that…
• The experiment provides a new insight into the relationship between…
• These results should be taken into account when considering how to…
• The data contribute a clearer understanding of…
• While previous research has focused on  x , these results demonstrate that y .

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Even the best research has its limitations. Acknowledging these is important to demonstrate your credibility. Limitations aren’t about listing your errors, but about providing an accurate picture of what can and cannot be concluded from your study.

Limitations might be due to your overall research design, specific methodological choices , or unanticipated obstacles that emerged during your research process.

Here are a few common possibilities:

• If your sample size was small or limited to a specific group of people, explain how generalizability is limited.
• If you encountered problems when gathering or analyzing data, explain how these influenced the results.
• If there are potential confounding variables that you were unable to control, acknowledge the effect these may have had.

After noting the limitations, you can reiterate why the results are nonetheless valid for the purpose of answering your research question.

• The generalizability of the results is limited by…
• The reliability of these data is impacted by…
• Due to the lack of data on x , the results cannot confirm…
• The methodological choices were constrained by…
• It is beyond the scope of this study to…

Based on the discussion of your results, you can make recommendations for practical implementation or further research. Sometimes, the recommendations are saved for the conclusion .

Suggestions for further research can lead directly from the limitations. Don’t just state that more studies should be done—give concrete ideas for how future work can build on areas that your own research was unable to address.

• Further research is needed to establish…
• Future studies should take into account…
• Avenues for future research include…

If you want to know more about AI for academic writing, AI tools, or research bias, make sure to check out some of our other articles with explanations and examples or go directly to our tools!

Research bias

• Anchoring bias
• Halo effect
• The Baader–Meinhof phenomenon
• The placebo effect
• Nonresponse bias
• Deep learning
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• Reinforcement learning
• Supervised vs. unsupervised learning

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In the discussion , you explore the meaning and relevance of your research results , explaining how they fit with existing research and theory. Discuss:

• Your  interpretations : what do the results tell us?
• The  implications : why do the results matter?
• The  limitation s : what can’t the results tell us?

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

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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McCombes, S. (2023, July 18). How to Write a Discussion Section | Tips & Examples. Scribbr. Retrieved August 7, 2024, from https://www.scribbr.com/dissertation/discussion/

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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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• 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 ,
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• 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,
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• 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 …

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Research Question Examples 🧑🏻‍🏫

25+ Practical Examples & Ideas To Help You Get Started 

By: Derek Jansen (MBA) | October 2023

A well-crafted research question (or set of questions) sets the stage for a robust study and meaningful insights.  But, if you’re new to research, it’s not always clear what exactly constitutes a good research question. In this post, we’ll provide you with clear examples of quality research questions across various disciplines, so that you can approach your research project with confidence!

Research Question Examples

• Psychology research questions
• Business research questions
• Education research questions
• Healthcare research questions
• Computer science research questions

Examples: Psychology

Let’s start by looking at some examples of research questions that you might encounter within the discipline of psychology.

How does sleep quality affect academic performance in university students?

This question is specific to a population (university students) and looks at a direct relationship between sleep and academic performance, both of which are quantifiable and measurable variables.

What factors contribute to the onset of anxiety disorders in adolescents?

The question narrows down the age group and focuses on identifying multiple contributing factors. There are various ways in which it could be approached from a methodological standpoint, including both qualitatively and quantitatively.

Do mindfulness techniques improve emotional well-being?

This is a focused research question aiming to evaluate the effectiveness of a specific intervention.

How does early childhood trauma impact adult relationships?

This research question targets a clear cause-and-effect relationship over a long timescale, making it focused but comprehensive.

Is there a correlation between screen time and depression in teenagers?

This research question focuses on an in-demand current issue and a specific demographic, allowing for a focused investigation. The key variables are clearly stated within the question and can be measured and analysed (i.e., high feasibility).

Examples: Business/Management

Next, let’s look at some examples of well-articulated research questions within the business and management realm.

How do leadership styles impact employee retention?

This is an example of a strong research question because it directly looks at the effect of one variable (leadership styles) on another (employee retention), allowing from a strongly aligned methodological approach.

What role does corporate social responsibility play in consumer choice?

Current and precise, this research question can reveal how social concerns are influencing buying behaviour by way of a qualitative exploration.

Does remote work increase or decrease productivity in tech companies?

Focused on a particular industry and a hot topic, this research question could yield timely, actionable insights that would have high practical value in the real world.

How do economic downturns affect small businesses in the homebuilding industry?

Vital for policy-making, this highly specific research question aims to uncover the challenges faced by small businesses within a certain industry.

Which employee benefits have the greatest impact on job satisfaction?

By being straightforward and specific, answering this research question could provide tangible insights to employers.

Examples: Education

Next, let’s look at some potential research questions within the education, training and development domain.

How does class size affect students’ academic performance in primary schools?

This example research question targets two clearly defined variables, which can be measured and analysed relatively easily.

Do online courses result in better retention of material than traditional courses?

Timely, specific and focused, answering this research question can help inform educational policy and personal choices about learning formats.

What impact do US public school lunches have on student health?

Targeting a specific, well-defined context, the research could lead to direct changes in public health policies.

To what degree does parental involvement improve academic outcomes in secondary education in the Midwest?

This research question focuses on a specific context (secondary education in the Midwest) and has clearly defined constructs.

What are the negative effects of standardised tests on student learning within Oklahoma primary schools?

This research question has a clear focus (negative outcomes) and is narrowed into a very specific context.

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Examples: Healthcare

Shifting to a different field, let’s look at some examples of research questions within the healthcare space.

What are the most effective treatments for chronic back pain amongst UK senior males?

Specific and solution-oriented, this research question focuses on clear variables and a well-defined context (senior males within the UK).

How do different healthcare policies affect patient satisfaction in public hospitals in South Africa?

This question is has clearly defined variables and is narrowly focused in terms of context.

Which factors contribute to obesity rates in urban areas within California?

This question is focused yet broad, aiming to reveal several contributing factors for targeted interventions.

Does telemedicine provide the same perceived quality of care as in-person visits for diabetes patients?

Ideal for a qualitative study, this research question explores a single construct (perceived quality of care) within a well-defined sample (diabetes patients).

Which lifestyle factors have the greatest affect on the risk of heart disease?

This research question aims to uncover modifiable factors, offering preventive health recommendations.

Examples: Computer Science

Last but certainly not least, let’s look at a few examples of research questions within the computer science world.

What are the perceived risks of cloud-based storage systems?

Highly relevant in our digital age, this research question would align well with a qualitative interview approach to better understand what users feel the key risks of cloud storage are.

Which factors affect the energy efficiency of data centres in Ohio?

With a clear focus, this research question lays a firm foundation for a quantitative study.

How do TikTok algorithms impact user behaviour amongst new graduates?

While this research question is more open-ended, it could form the basis for a qualitative investigation.

What are the perceived risk and benefits of open-source software software within the web design industry?

Practical and straightforward, the results could guide both developers and end-users in their choices.

Remember, these are just examples…

In this post, we’ve tried to provide a wide range of research question examples to help you get a feel for what research questions look like in practice. That said, it’s important to remember that these are just examples and don’t necessarily equate to good research topics . If you’re still trying to find a topic, check out our topic megalist for inspiration.

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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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Dissertation Recommendations — How To Write Them

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Recommendations are crucial to your paper because they suggest solutions to your research problems. You can include recommendations in the discussion sections of your writing and briefly in the conclusions of your dissertation , thesis, or research paper . This article discusses dissertation recommendations, their purpose, and how to write one.

Inhaltsverzeichnis

• 1 Dissertation Recommendations — In a Nutshell
• 2 Definition: Dissertation recommendations
• 3 How to write dissertation recommendations
• 4 Dissertation recommendations based on your findings
• 5 Purpose of dissertation recommendations

Dissertation Recommendations — In a Nutshell

• Dissertation recommendations are an important aspect of your research paper.
• They should be specific, measurable, and have the potential of future possibilities.
• Additionally, these recommendations should offer practical insights and suggestions for solving real-life problems.

When making your recommendations, please ensure the following:

• Your recommendations are an extension of your work instead of a basis for self-criticism
• Your research stands independently instead of suggesting recommendations that will complete it
• Your dissertation recommendations offer insights into how future research can build upon it instead of undermining your research

Definition: Dissertation recommendations

Dissertation recommendations are the actionable insights and suggestions presented after you get your research findings. These suggestions are usually based on what you find and help to guide future studies or practical applications. It’s best to place your dissertation recommendations at the conclusion.

How to write dissertation recommendations

When writing your academic paper, you can frame dissertation recommendations using one of the following methods:

Use the problem: In this approach, you should address the issues highlighted in your research.

Offer solutions: You can offer some practical solutions to the problems revealed in your research.

Use a theory: Here, you can base your recommendations on your study’s theoretical approach.

Here are some helpful tips for writing dissertation recommendations that you should incorporate when drafting a research paper:

• Avoid general or vague recommendations
• Be specific and concrete
• Offer measurable insights   Ensure your suggestions are practical and implementable
• Avoid focusing on theoretical concepts or new findings but on future possibilities

“Based on the study’s outcomes, it’s recommended that businesses and organizations develop mental health well-being frameworks to reduce workplace stress. This training should be mandatory for all employees and conducted on a monthly basis.”

Dissertation recommendations based on your findings

After analysing your findings, you can divide your dissertation recommendations into two subheadings as discussed below:

What can be done?

This section highlights the steps you can use when conducting the research. You may also include any steps needed to address the issues highlighted in your research question. For instance, if the study reveals a lack of emotional connection between employees, implementing dynamic awareness training or sit-downs could be recommended.

Is further research needed?

This section highlights the benefits of further studies that will help build on your research findings. For instance, if your research found less data on employee mental well-being, your dissertation recommendations could suggest future studies.

Purpose of dissertation recommendations

Note: Dissertation recommendations have the following purposes:

• Provide guidance and improve the quality of further studies based on your research findings
• Offer insights, call to action, or suggest other studies
• Highlight specific, clear, and realistic suggestions for future studies

When writing your dissertation recommendations, always remember to keep them specific, measurable, and clear. You should also ensure that a comprehensible rationale supports these recommendations. Additionally, your requests should always be directly linked to your research and offer suggestions from that angle.

Note that your suggestions should always focus on future possibilities and not on present new findings or theoretical concepts. This is because future researchers may use your results to draw further conclusions and gather new insights from your work.

Can I include new arguments in the conclusion of a dissertation

Dissertations follow a more formal structure; hence, you can only present new arguments in the conclusion. Use your dissertation’s concluding part as a summary of your points or to provide recommendations.

How is the conclusion different from the discussion sections?

The discussion section describes a detailed account of your findings, while the conclusion answers the research question and highlights some recommendations.

What shouldn't I include in the dissertation recommendations?

Avoid concluding with weak statements like “there are good insights from both ends…”, generic phrases like “in conclusion…” or evidence that you failed to mention in the discussion or results section.

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Using future research suggestions as a basis to come up with a dissertation topic idea

To use future research suggestions as a basis to come up with a dissertation topic idea, you need to have read a journal article on a topic that interests you. Having read this journal article, focus on the section at the end of the article, often called Future Research (or Discussion/Research Limitations ), where the authors not only tend to criticise their work, but also propose future research that could address such problems. Now, follow the five steps below:

• STEP ONE: Identify the types of future research suggestion discussed by the authors
• STEP TWO: Understand the potential relationship between these future research suggestions and what makes a dissertation topic significant
• STEP THREE: Critique the future research suggestions
• STEP FOUR: Choose a future research suggestion that you feel you can build on ; and that interests you
• STEP FIVE: Turn your dissertation idea into a purpose statement

STEP ONE Identify the types of future research suggestion discussed by the authors

Authors of good journal articles will make a number of future research suggestions in their work. These may include one or more of the following types of future research suggestion:

Addressing research limitations in their research

All research has limitations . These may include: (a) an inability to answer research questions; (b) theoretical and conceptual problems; (c) limitations in the research strategy adopted; and (d) problems of research quality. The desire of authors to address research limitations in their research is one of the most common types of future research suggestion you will come across.

Building on a particular finding in their research

There are often findings that come out of the research process that the authors did not anticipate at the start of the research process. These findings can help authors to propose entirely new avenues to explore in future studies. As a result, future research suggestions are sometimes based on building on a particular finding from the authors? research.

Re-evaluating or expanding a conceptual framework (or theoretical model)

Research rarely tries to build grand theories or examine very broad conceptual frameworks. There are a number of reasons for this. Perhaps the most obvious is the difficultly in demonstrating the quality of the findings . When we talk about problems of research quality , we are referring to the difficult (or inability) of researchers to prove that their findings are reliable and externally valid (in quantitative research designs) or confirmable, credible, dependable, and transferable (in qualitative research designs) [see the section on Research Quality for more information]. This means that most high quality research focuses on tackling research questions within a particular context , location and/or culture . Tackling research in this way means that there are many ways to re-evaluate or expand on the conceptual framework (or theoretical model) that authors used to strength and/or underpin their research. For example, authors may suggest that future research could involve no more than taking their existing research and applying it to a new context, location and/or culture to examine if it was still applicable. As a result, you will often see authors making future research suggestions that are based on re-evaluating or expanding a conceptual framework (or theoretical model ).

For a more detailed overview of these future research suggestions, see the article: Types of future research suggestion . Within the Research Limitations section of this website, we also go into more detail on each of these types of future research suggestions. Reading these articles will help you to identify what types of future research suggestions are being discussed by the authors in the journal article you are interested in.

STEP TWO Understand the potential relationship between these future research suggestions and what makes a dissertation topic significant

Whilst dissertations are rarely "ground-breaking" at the undergraduate or master's level (and are not expected to be), they should still be significant in some way. When coming up with a dissertation topic idea, you need to be able to explain how your idea is significant. Your research may be significant in one or a number of ways. It may:

Capitalise on a recent event

Reflect a break from the past

Target a new audience

Address a flaw in a previous study

Expand a particular field of study

Help an individual, group, organisation, or community

Since this section of the article deals with using future research suggestions as a basis for coming up with a dissertation topic idea, just two of these aspects of research significance are relevant:

The desire to address a flaw in a previous study.

The desire to expand a particular field of study.

Improving the Nation's Water Security: Opportunities for Research (2007)

Chapter: 6 recommendations for future research directions, 6 recommendations for future research directions.

Progress has been made in the Environmental Protection Agency’s (EPA’s) water security research program (see Chapter 4 ), but many important research questions and technical support needs remain. In Chapter 3 , a framework is suggested for evaluating water security research initiatives that gives priority to research that improves response and recovery and/or develops risk reduction or consequence mitigation measures. The research should also produce tools with a reasonable likelihood of implementation and, where feasible, dual-use benefits. Based on this framework and the review of water security efforts already under way, two important water security research gaps are identified and discussed briefly in this chapter. In addition, short- and long-term water security research recommendations are made. The research recommendations are organized in this chapter according to the three long-term program objectives proposed in Chapter 5 emphasizing pre-incident, incident, and post-incident applications: (1) develop products to support more resilient design and operation of facilities and systems, (2) improve the ability of operators and responders to detect and assess incidents, and (3) improve response and recovery. Both drinking water and wastewater research priorities are addressed together within these three objectives to maximize research synergies that may exist.

KEY RESEARCH GAPS

The Water Security Research and Technical Support Action Plan (EPA, 2004a) set out a comprehensive guide for the EPA’s near-term research initiatives. Although the Action Plan was intended to provide a short-term (three- to four- year) research agenda, the previous National Research Council review (NRC, 2004) noted that several of the Action Plan projects represented long-term research questions not easily ad-

dressed in the original time frame. Therefore, the Action Plan provides a reasonable starting point for building the EPA’s future research program. Nevertheless, the short-term planning horizon of the Action Plan prevented consideration of two key subjects that are critical to a long-term water security research program: behavioral science and innovative system design. The committee recommends the EPA work in collaboration with other organizations to build research initiatives in these two areas.

Behavioral Science

The threat of bioterrorism presents new and different types of risks that are dynamic and pose difficult trade-offs, bringing about intellectual challenges and an emotional valence possibly more important than the risks themselves. Developing an effective communication strategy that meets the needs of the broad range of stakeholders (e.g., response organizations, water organizations and utilities, public health agencies, the public, the media) while addressing security concerns is clearly a high-priority research area. The EPA’s work on risk communication is focused primarily on the development of guidance, protocols, and training, and little emphasis has been devoted to interdisciplinary behavioral science research to better prepare stakeholders for water security incidents or to build confidence in their ability to respond. Behavioral science research could help address, for example, what the public’s beliefs, opinions, and knowledge about water security risks are; how risk perception and other psychological factors affect responses to water-related events; and how to communicate these risks with the public (Gray and Ropeik, 2002; Means, 2002; Roberson and Morely, 2005b). A better understanding of what short-term disruptions customers are prepared to tolerate may also guide response and recovery planning and the development of recovery technologies.

Previous experience with natural disasters and environmental risks provides a basis for investigating and predicting human behavior in risky situations (Fischoff, 2005). Existing models of human behavior during other kinds of crises, however, may not be adequate to forecast human behavior during bioterrorism or water security incidents (DiGiovanni et al., 2003).

Risk communicators consider empirical findings from psychology, cognitive science, communications, and other behavioral and social sciences to varying extents (Bostrom and Lofstedt, 2003). Although decision makers frequently predict panic and irrational behavior in times of

crisis, behavioral science researchers have found that people respond reasonably to such challenges (e.g., Fishoff, 2005). Given the urgency of terror risk communication, risk communicators are obliged to incorporate existing behavioral science research as it relates to water security risks.

The EPA should take advantage of existing behavioral science research that may be applicable to water security issues, but this requires knowledge and experience in behavioral science research. Where gaps exist, the EPA will need to engage in interdisciplinary, rigorous empirical research to obtain the necessary knowledge.

Innovative Designs for Secure and Resilient Water and Wastewater Systems

Innovative designs for water and wastewater infrastructure were not addressed in the EPA Action Plan, but the topic deserves a place in a long-term water security research program. The EPA’s research mission has traditionally included the development and testing of new concepts, technologies, and management structures for water and wastewater utilities to achieve practical objectives in public health, sustainability and cost-effectiveness. The addition of homeland security to its mission provides a unique opportunity to take a holistic view of current design and management of water and wastewater infrastructures. Innovation is needed to address the problem of aging infrastructures while making new water systems more resilient to natural hazards and malicious incidents. The EPA should, therefore, take a leadership role in providing guidance for the planning, design, and implementation of new, more sustainable and resilient water and wastewater facilities for the 21st century.

Disagreggation of large water and wastewater systems should be an overarching theme of innovation. Large and complex systems have developed in the United States following the pattern of urban and suburban sprawl. While there are clear economies of scale for large utilities in construction and system management, there are distinct disadvantages as well. The complexity of large systems makes security measures difficult to implement and complicates the response to an attack. For example, locating the source of incursion within the distribution system and isolating contaminated sections are more difficult in large and complex water systems. Long water residence times are also more likely to occur in large drinking water systems, and, as a result, disinfectant residual may be lacking in the extremities of the system because of the chemical and biological reactions that occur during transport. From a security perspec-

tive, inadequate disinfectant residual means less protection against intentional contamination by a microbial agent.

A breadth of possibilities exists for improving security through innovative infrastructure design. Satellite water treatment plants could boost water quality. Strategic placement of treatment devices (e.g., ultraviolet lamp arrays) within the distribution system could counter a bioterrorism attack. Wastewater treatment systems could be interconnected to provide more flexibility in case of attack, and diversion devices could be installed to isolate contaminants. Box 6-1 describes some of these concepts in greater detail, and specific research recommendations are suggested in the following section.

RESEARCH RECOMMENDATIONS: DEVELOP PRODUCTS TO SUPPORT MORE RESILIENT DESIGN AND OPERATION OF FACILITIES AND SYSTEMS

Specific research topics are suggested here in two areas to support development of more resilient water and wastewater systems: (1) innovative designs for water and wastewater and (2) improved methods for risk assessment, including processes for threat and consequence assessments.

Innovative Designs for Water and Wastewater Systems

Innovative changes to water infrastructure will require long-term investment in research. Existing systems have been in place for more than a century in older cities. Thus, bold new directions will understandably require intensive research at the outset to produce a defensible economic argument for change. On the other hand, the EPA has the opportunity to develop innovative approaches that can be implemented almost immediately in relatively new, as well as planned, urban and suburban areas. The first step in research would be to enumerate the opportunities for innovation, recognizing the constraints brought about by the size, age, and complexity of existing water and wastewater infrastructures. A broad-gauge, economic analysis should follow that would quantify the costs and multiple benefits of these innovative designs (e.g., increased security, improved drinking water quality, enhanced sustainability of water resources). In addition, there is an implicit need for EPA research-

ers to coordinate with the agency’s regulatory branch to validate the feasibility of the innovative concepts that are proposed.

Each of the infrastructure concepts illustrated in Box 6-1 require far more research to become feasible. The recommendations below outline specific research topics that, if addressed, could improve the safety and sustainability of water resources in the 21st century.

Disaggregation of Water and Wastewater Systems

The “distributed optimal technology network” (DOT-Net) concept (Norton and Weber, 2005; Weber, 2002; 2004) hinges upon the feasibility of distributed treatment via point-of-use (POU)/point-of-entry (POE) devices installed at the scale of individual buildings or perhaps small neighborhoods. The corollary premise is that installation of expensive advanced treatment technology at the centralized water treatment facility is unnecessary when only a fraction of the service area outside a “critical radius” requires additional protection. Only a broad economic analysis of this concept has been published thus far for a hypothetical urban center, but the assumptions need to be verified for actual systems, particularly because of the unique characteristics of individual cities. In addition, far more research is needed on the utility management required to ensure the reliability of POU/POE devices in widespread implementation.

Dual water systems have also been proposed to address aging infrastructure (see Box 6-1 ; Okun, 1997; 2005). As with the DOT-Net concept, long-term research is needed to determine the costs and benefits of constructing an entirely new paradigm for distribution system design. Research issues would include assessing the acceptability of reclaimed water for progressively more intense levels of nonpotable use (e.g., irrigation, toilet flushing, laundering), the acceptability and management demands of decentralized wastewater treatment facilities, and the net benefits to water security.

In-Pipe Interventions to Reduce Exposure

In-pipe engineering interventions (see Box 6-1 ) are deserving of research in a long-term water security research strategy. For example, research is needed to optimize the location of disinfection booster stations or to examine the effectiveness and feasibility of in situ ultraviolet (UV)

irradiation systems as a decontamination strategy. EPA research could also examine various pipe materials (e.g., stainless steel) and evaluate their benefits for security and sustainability relative to their costs.

Infrastructure Designs to Enable Isolation and Interconnection

Most large drinking water systems have the ability to isolate portions of their distribution systems during necessary system repairs, but security concerns provide a new impetus for rapid and effective isolation mechanisms. Research on innovative mechanisms to isolate or divert contaminated water in drinking water and wastewater systems would be useful. The EPA should identify these design options, research their costs and benefits (including dual-use benefits) and their feasibility both for existing systems and new infrastructure, and make this information available to system managers.

Improved Risk Assessments Procedures

A sound risk assessment process allows utilities to make better resource management decisions for enhancing their recovery capacity or security strategies to mitigate the consequences of an attack. The risk assessment process includes assessments of threat, consequences, and vulnerability. To date, most of the efforts to guide utilities in their own risk assessments have focused on vulnerabilities.

Threat Assessment

Water and wastewater utilities today are making resource management decisions related to security without adequate information about the nature and likelihood of threats to their systems. As discussed in Chapter 4 , the EPA has focused their efforts on identifying contaminant threats without conducting similarly detailed analyses of possible physical and cyber threats. Both the nature and likelihood of these threats are needed for efficient allocation of resources at the utility level and within the EPA’s research program. Improved threat assessment would require the EPA and/or a consortium of water experts to work closely with the intelligence community and local law enforcement agencies. Other national and federal laboratory expertise within the Department of Energy,

Department of Defense, and private-public community might be needed as well. Threat assessments for water and wastewater should be periodically reviewed to identify threat scenarios that should be added to the list and to remove those that are no longer a concern. The development of a threat assessment process for local water and wastewater utilities with current techniques used in other infrastructures would also be helpful, provided the threat information could be communicated to those who need it (ASME, 2004; Sandia National Laboratories, 2001).

Consequence Assessment

A consequence assessment should accompany the threat assessment within the risk assessment process. Consequence assessments would provide decision makers with information on the potential for fatalities, public health impacts, economic impacts, property damage, systems disruption, effects on other infrastructures, and loss of public confidence. Procedures for determining the expected consequences from an attack or natural disaster are not currently being systematically developed. As a result, water system managers do not have sufficient data to make decisions about the benefits of risk reduction relative to the costs. The development and application of a consequence assessment procedure would provide decision makers with information needed to decide whether to mitigate the consequences, upgrade with countermeasures, take steps to improve response and recovery capacity, and/or decide to accept the level of risk and take no further action. A fault tree analysis that includes, for example, options for redundant systems or contingency water supplies could provide vital information on whether to invest in security upgrades or less costly consequence mitigation strategies . Many of these approaches have already been developed for other infrastructures (e.g., Risk Assessment Methodology [RAM]-T for the high-voltage power transmission industry or RAM-D for dams, locks, and levees; see Sandia National Laboratories, 2001; 2002). A thorough review of other RAM methodologies could provide guidance for consequence assessment strategies that could be incorporated into the Risk Assessment Methodology for Water Utilities (RAM-W).

The EPA has worked to develop the AT Planner tool to assist utilities in assessing the consequences from physical attacks (see Chapter 4 ). While AT Planner has been validated against actual blast test data for nonwater systems, there remains significant uncertainty in the applicability of the modeling for water security because it has not been validated

against the structures specific to those systems. Therefore, the ongoing evaluation of AT Planner by the EPA and select water utility operators should include an assessment of the applicability of AT Planner for each of the critical and high-consequence components of a water system. The EPA and water utilities should then consider whether any additional validation testing is needed to determine specific failure modes of relevant water system components (e.g., actual storage tanks, pumps, water conduits, chlorine tanks) and possible countermeasures.

Summary of Research Priorities for Secure and Resilient Systems

Short-term priorities.

Develop an improved understanding of physical, cyber, and contaminant threats to water and wastewater systems, especially focusing on physical and cyber threats.

Communicate information on threats and consequences to water system managers through training and information exchange.

Develop an improved threat assessment procedure for water and wastewater utilities that will assist local utilities with their security and response planning.

Develop a process to assist local utilities in determining the consequences from physical, cyber, and contaminant attacks.

Update the risk assessment methodology for water systems to incorporate the latest approaches used in other industries, including developing credible threat descriptions and identifying cascading consequences.

Long-Term Priorities

Develop innovative design strategies for drinking water and wastewater systems that mitigate security risks and identify their costs and benefits in the context of public health, sustainability, cost-effectiveness, and homeland security. These designs might include:

In-pipe intervention strategies for drinking water systems,

Disaggregation of water and wastewater treatment facilities to achieve dual-use benefits, and

Designs that allow for interconnections and isolation.

Evaluate the need to validate AT Planner against structures specific to water systems.

Periodically review the EPA’s prioritized list of threats, contaminants, and threat scenarios to identify items that should be added to the list and remove items that are no longer a concern.

Continue development of technology transfer/training programs so that utilities understand the value of the EPA’s products for both homeland security incidents and natural disasters and know how to utilize the tools to their full extent.

Implementation of Priorities

Some of the research recommendations to support more resilient design and operation of drinking water and wastewater systems lie outside of the EPA’s traditional areas of expertise. To support the Action Plan efforts so far, the EPA has relied heavily on expert contractors to conduct this type of work. The EPA should continue to seek the relevant expertise of other federal agencies and national laboratories in these future efforts. However, the EPA will need to consider how best to balance intramural and extramural research funding to carry out this research, while maintaining appropriate oversight and input into the research activities (see also Chapter 5 ). Increasing staff expertise in some key areas, such as physical security, will be necessary to build a strong and well-rounded water security research program to support more resilient system design and operation.

RESEARCH RECOMMENDATIONS: IMPROVE THE ABILITY OF OPERATORS AND RESPONDERS TO DETECT AND ASSESS INCIDENTS

Suggestions are provided in this section for future research that should improve the ability of operators and responders to detect and assess water security incidents. Specific research suggestions in the areas of analytical methodologies and monitoring and distribution system modeling are discussed below.

Analytical Methodologies and Monitoring

Expanding existing analytical methods.

For some analytes of relevance to water security concerns, the available or approved detection methods are poor (e.g., some nonregulated analytes). More work needs to be done to expand existing methods to a broader range of analytes. For example, method 300.1 (EPA, 2000) covers only the common anions but could be extended to others, including toxic substances. The extension of existing methods to new analytes would allow a broader range of laboratories to expand their capabilities into the water security area.

Screening methods using conventional gas chromatography (GC) or high-performance liquid chromatography (HPLC) should also be investigated. Modern high-resolution chromatography combined with high-sensitivity detection (e.g., electron capture, fluorescence) is a powerful, yet accessible tool. Protocols should be developed to make the best use of these widely available capabilities. Software will have to be developed to facilitate the documentation of normal, background signals (fingerprint-type chromatograms). This background information can then be used to detect anomalies. Final protocols would have to be tested thoroughly against priority chemical contaminants. Chromatographic finger-prints have been used to monitor water supplies for nonintentional contamination, so this line of research would provide a dual benefit (D. Metz, Ohio River, personal communication, 2006; P. Schulhof, Seine River, personal communication, 2006).

Progress is being made with the protocol to concentrate samples and identify biological contaminants by polymerase chain reaction (PCR) analysis. Continued research, however, needs to be directed towards reducing the time and effort required to collect, process, and identify samples by automating portions of the protocol such as the concentration step. Such automated collection and sample processing systems would be especially valuable in response to security threats, when water samples could be channeled to existing or new detection technologies capable of onsite processing. The EPA should continue to expand the number of biothreat agents tested with the concentration/PCR protocol to include microbes other than spores, prioritizing test organisms that are both a threat to public health and resistant to chlorine (Morales-Morales, et al., 2003; Straub and Chandler, 2003). Continued testing of the concentration/PCR protocol should include various mixed suspensions of a target

microbe and background microbes to determine specificity of detection and various dilutions of the target microbe to determine sensitivity of detection. The protocol should also be tested on chloraminated water samples.

Developing New Monitoring Technologies

Chemical Detection. New chemical monitoring technologies for security-relevant analytes should be investigated. Examples include quartz crystal microbalance (QCM) sensors, microfluidic devices (lab-on-a-chip), ion-sensitive field-effect transistors (ISFETs), and larger-scale optrodes. Extramural agency and corporate partnerships developed by the EPA and longer-term research projects will help the evaluation and consideration of a broader range of detection platforms.

Biological Detection. Biological monitoring devices are essential to assess the type and extent of contamination in a suspected water security event. A broader range of innovative and developing detection technologies for biological agents, including methods that are field deployable and reagent-free, should be considered and evaluated. Innovative, field-deployable detection technologies (e.g., genetic fingerprinting, immunodetection, other technologies in development by universities, the Department of Defense, and industry) could reduce the time and effort for detection and enable earlier response efforts (Iqbal et al., 2000; Ivnitski et al., 2003; Lim et al., 2005; Monk and Walt, 2004; Yu and Bruno, 1996; Zhu et al., 2004). These new technologies might also increase the accuracy of detecting deliberate contamination events and reduce false alarms. Methods that can detect multiple biological agents and those with dual-use benefits should be emphasized over those methods limited to very specific agents (Peruski and Peruski, 2003; Rogers and Mulchandani, 1998). For example, DNA fingerprinting might be more useful than immunodetection systems dependent on a highly specific antibody for operation. The accuracy of these detection methods will depend on availability of quality reagents such as antibodies and primers; therefore, researchers will need to work closely with the Centers for Disease Control and Prevention (CDC) and other agencies that have access to such reagents.

Monitoring Devices for Wastewater Collection Systems . Contamination incidents have the potential to disrupt wastewater biological treat-

ment systems; thus, a long-term research program should also include research on monitoring technologies relevant to wastewater security concerns. Although a number of devices are available that can be used to monitor physical, chemical, and biological parameters, none of the currently available devices are robust or reliable enough when used in untreated wastewater to meet security requirements. The EPA should, therefore, encourage development of robust or reliable monitoring devices for wastewater infrastructure.

Syndromic Surveillance Tools. Syndromic surveillance tools may have the potential for detecting disease outbreaks and for investigating the possible role of water in such outbreaks (Berger et al., 2006). The EPA is already working to test two syndromic disease surveillance tools (RODS, ESSENCE) against prior water contamination outbreak data. There are substantive research needs that should be undertaken, however. Clearly, the improvement of existing syndromic surveillance tools is a long-term research objective. For syndromic surveillance to become worthwhile, it should achieve a favorable cost-benefit ratio considering the costs of false positives, and syndromic surveillance should also be adequately integrated into response plans. The implementation of syndromic surveillance systems on a large scale would require a more detailed linkage between disparate databases used in the public health sector and the water supply sector. Research to develop tools to allow local systems to readily fuse information from these disparate sources would be desirable. Such linkages would improve detection and response to waterborne disease outbreaks and more rapidly exclude water as a possible vehicle of disease. This would have important applications for both intentional and nonintentional water contamination events.

Real-Time Monitoring Systems

The development of a fully functional, easy-to-maintain, real-time monitoring system (RTMS) that could someday be used to prevent harm from deliberate attacks on the water system (“detect to prevent”), even with substantial research investments, is many years away. Therefore, the primary emphasis of future research on RTMSs, at least in the near term, should be on developing these technologies to assess the spread of contaminants, not to prevent exposure.

The committee also questions the likelihood of implementation of real-time monitoring devices for specific chemical or biological parame-

ters that are not useful in the day-to-day operation of a system (see Chapters 2 and 4 ). However, there are a few scenarios where implementation of continuous monitors for biological contaminants might be valuable, such as their use in certain water systems under heightened threat conditions (e.g., utilities for which specific intelligence information indicates they may be targeted). As discussed in Chapter 4 , deployment under these circumstances has a greater likelihood for success because the probability of an event is estimated to be much higher and the length of monitoring time is shortened. The use of highly sensitive and specific detection devices under such targeted circumstances would significantly lower the probability of false alarms and reduce the problem of poor positive predictive value (see Chapter 2 ) while also minimizing implementation and maintenance costs. Thus, improving monitoring systems for specific chemical or biological agents in drinking water is a valid long-term research goal. The EPA may find that longer-term research on more speculative sensor development could benefit from a further broadening of the circle of collaborators. Such speculative research may be more appropriately funded through the National Science Foundation or the Homeland Security Advanced Research Projects Agency, thus freeing up EPA resources for other purposes. To encourage such research, the EPA may wish to build its connections with the private sector on this technology.

Research on detection methods for RTMSs should proceed with careful consideration of the likelihood of implementation of the monitoring devices. In its near-term research plans, the EPA should adopt a first-stage approach to RTMSs, emphasizing generic sensors to detect intrusion or a system anomaly. The intrusion detection would then trigger more resource-intensive follow-up monitoring and analysis. Such an approach has significant dual-use benefits for routine contamination events that could outweigh the costs of implementing and operating these systems. Additional effort to develop cheaper, more accurate, and more easily deployable and maintainable sensors for routine water quality parameters would be useful both for anomaly detection and routine operation. Additional research is also needed, even in first-stage RTMSs, to understand normal water quality variations and distinguish variations that might be caused by a deliberate contamination attack. For example, continuous monitoring of chlorine residual at multiple points in the distribution system often reveals wide variations at different temporal scales due to changes in water demand that affect water residence time (e.g., operation of storage tanks). Although some work to understand inherent water quality variability in distribution systems is being conducted through the

Water Sentinel program, a significant amount of work is needed to translate the findings of this research into criteria for RTMSs to develop systems that have a reasonable likelihood of implementation.

An important component of RTMS research should include data fusion, whereby multiple anomalies must occur before an alarm signal is sent (see also Chapter 4 ). The private sector seems to be taking the lead on many types of multiparameter approaches to RTMSs and the processing of data, especially as described by contaminant or event signatures. It is important that the algorithms are open to peer review and can be accessed by all for development of new and refined approaches.

RTMS sensor research should consider a broader range of technologies, including full-spectrum UV and visible absorption, fluorescence excitation emission matrices, and ionization sensors (Alupoaei et al., 2004; Fenselau and Demirev, 2001; Lay, 2001). Many of these techniques are used as nonspecific chromatography detectors, and as such, they are highly sensitive. Most prototype RTMSs are composed of existing sensors that are designed to measure a specific contaminant, and some technologies have been excluded because they have not led to sensors with a high degree of selectivity. However, RTMSs need not be contaminant-specific; they only need to detect anomalies. Detection of an anomaly can then be followed by more specific contaminant analyses.

The problem of false positive signals from real-time contaminant-specific warning systems has been discussed in Chapter 2 . In essence, the problem is one of unfavorable arithmetic when the probability of a true positive is very small, as it would be for an intentional contamination attack on any particular water system of the tens of thousands of such systems. Therefore, most contaminant-specific alarm signals will be false positives. The EPA should consider the consequences of various rates of false positive signals for both large and small utilities and collect information on how alarms are currently handled by utilities. Workshops and structured surveys on this issue would provide valuable information on current practices, the extent to which positive signals are confirmed, the costs of false alarms, and the views of utility operators on their tolerance for various levels and types of false alarms. This research would provide useful guidance for the developers of water quality monitoring devices, for utilities that are considering implementing devices that are commercially available, and for local and state regulatory agencies who will need assistance interpreting alarm signals in light of the public health consequences.

Technology Testing

The EPA has developed a rigorous technology testing program to provide security product guidance to end users focusing on monitoring and decontamination technology. However, as noted in Chapter 4 , the number of relevant security technologies and agents of interest exceed the capacity and budget of the Technology Testing and Evaluation Program (TTEP). Therefore, developing a test-prioritization plan for TTEP seems especially important and is strongly recommended. Although the process of identifying technologies of interest has begun through the use of stakeholder meetings and advisory boards, activities to date have been weighted toward doing the easiest things first, and only some of these tests provided dual-use benefits. Balancing the homeland security benefits and the benefits to routine water system operations in TTEP will likely require additional strategic planning. One strategy has been to test equipment that is commercially available regardless of whether it addresses a high-risk agent. Instead, the EPA should look beyond the easy-to-identify commercially available equipment and make a greater effort to identify technologies in development that have the potential to address those agents identified as posing the greatest risk to water, considering the likelihood of the threat (including the ease of acquiring particular chemical or biological agents), the potential consequences, and the likelihood of implementing the technology. For a few of the highest-priority threats, the EPA may wish to consider providing technical support and/or funding to encourage more rapid development of a particularly promising technology that has a high likelihood of implementation and significant dual-use benefits, similar to the EPA Superfund Innovative Technology Evaluation (SITE) Emerging Technology Program.

Develop Laboratory Capability and Capacity

Adequate laboratory capacity is critical for responding to a terrorist incident affecting water supplies, and although this is not a research issue, the EPA has much to contribute from an applied perspective. The need for mobile analysis units capable of supplementing local laboratories and rapidly responding to geographical areas impacted by terrorist events should be considered. Such mobile laboratories could also address analytical needs that arise during natural catastrophes, such as Hurricane Katrina. Many states have begun to develop mobile laboratory

capabilities as part of their water security activities, and the EPA could glean information on their experiences to date.

The EPA is working with utilities and state and federal agencies to build a national laboratory response network for water sample analysis (i.e., the Water Laboratory Alliance). Some university laboratories may have capabilities that could merit inclusion in the nationwide network. Other laboratories may be stimulated to conduct additional research on improved analytical methods for toxic and biothreat agents if they were better informed of the current state of knowledge and had access to reference standards (access to some reference standards is currently limited due to security concerns). To be successful, a dual-use philosophy should be adopted whenever possible in the development of laboratory capacity (e.g., employing methods/instruments that can also be used for standard analytes).

Distribution System Modeling Tools

Distribution system models provide valuable tools for locating the source of contamination or assessing the spread if the source is known, estimating exposure, identifying locations for sampling, and developing decontamination strategies (see also Chapter 4 ). Distribution system models also have important dual-use applications to routine water quality concerns, and the EPA should continue to emphasize the dual-use value of its modeling tools. Specific recommendations are provided below to advance the capabilities and implementation of the Threat Ensemble Vulnerability Assessment (TEVA) and EPANET models.

Experimental Verification of Species Interaction Subcomponent Models

The final goal of producing a more flexible EPANET model through Multi-Species EPANET (MS-EPANET) is commendable. However, the new subcomponents are based upon developing better fundamental knowledge of reactions within the distribution system involving chemistry (e.g., disinfection kinetics, chemical partitioning), biology (e.g., development of biofilms, release and attachment of microbes), and materials science (e.g., corrosion of pipe materials and its relationship to disinfection efficacy). The large number of system constants in both MS-EPANET and TEVA necessitate significant investment in sensitivity

analysis research to quantify the accuracy of model predictions. The development and testing of all new features of MS-EPANET should be a long-term research goal. Until the validity of these subcomponents is verified and system constants can be assigned with more certainty, the water industry will be reluctant to use the full capability of MS-EPANET. Limitations in the accuracy of model predictions will need to be addressed in guidance to decision makers. A significant commitment will be needed in resources for experimental verification.

Alternate Approaches to Uncertainty Modeling

The Action Plan acknowledges correctly that the distribution system model simulations should incorporate an analysis of uncertainty because the point of attack is unknown. This has led to the use of the well-known Monte Carlo analysis to randomize the location of the attack and run repeated distribution system model simulations (1,000 or more) to generate a probability distribution to relate point of attack to human exposure impact. The focus on short-term results, however, has produced weaknesses in the current EPA approach to uncertainty research.

A broader discussion about how to incorporate uncertainty into the TEVA model should be invited. Approaches such as fuzzy logic (McKone and Deshpande, 2005) and Bayesian Maximum Entropy modeling (Serre and Christakos, 1999) are showing promise but have been applied mainly to homogenous space rather than to network domains. The EPA should encourage alternative ideas for handling uncertainty. If the expertise is not available within the agency, there needs to be a mechanism to expand extramural support for research, particularly within the university community.

Technology Transfer and Training in Use of the TEVA and EPANET Models

Advances in the TEVA model add significant complexity to the EPANET model, which may limit its widespread implementation. The EPA should work to communicate the capabilities of EPANET, MS-EPANET, and TEVA to utilities, emphasizing their value for routine water quality concerns, advanced homeland security planning, and contamination assessment and response activities. Until TEVA and MS-EPANET are further developed and widely available, the EPA should

consider an interim strategy to better inform water utilities on the value and use of existing distribution system models, such as EPANET. Progressive water utilities are already using EPANET to examine possible locations of attack and to track the concentration of contaminants within the distribution system.

Training in the use of MS-EPANET and the proposed TEVA model is also needed. Water utility managers need to be convinced that the costs for adapting a new model for their respective distribution systems are worthwhile, because many utilities have already invested heavily in development, verification, and calibration of existing models. The complexity of the TEVA model may increase these costs further, because many more implementation steps follow those for EPANET to adapt the TEVA “template” to the specifics of each water utility.

Summary of Research Priorities for Better Equipping Operators to Detect and Assess Incidents

Automate the concentration step of the concentration/PCR protocol.

Continue to test the concentration/PCR protocol:

Expand the number of biothreat agents tested to four or five organisms that include microbes other than spores, focusing on microbes that are both a threat to public health and resistant to chlorine.

Test the concentration/PCR protocol with chloraminated water samples.

Test the concentration/PCR protocol to determine sensitivity and specificity of detection.

Field-test RTMSs to determine false positive/false negative rates and maintenance requirements and develop basic criteria for the technology that might lead to a reasonable likelihood of implementation.

Continue research to develop a first-stage RTMS based on routine water quality sensors with dual-use applications.

Analyze the consequences of false positive signals from realtime monitoring systems, emphasizing current practices, the extent to which positive signals are confirmed, the costs of false alarms, and the tolerance of utility operators for false alarms.

Test standard chromatographic methods for their ability to screen for a broad range of toxic agents in routine laboratory testing.

Develop a test-prioritization strategy for TTEP to optimize the resources devoted to this effort.

Invite external peer review of the TEVA model before investing in field testing.

Long-term Priorities

Continue to develop portable, field-deployable systems that can be used to collect and process samples at event locations.

Formulate protocols and develop software for using GC- and HPLC-based fingerprinting to detect suspicious anomalies.

Stimulate research and ultimately development of new sensors for water security analytes based on innovative technologies, such as QCM, ISFETS, and microfluidics.

Evaluate and develop new field-deployable detection technologies for biological agents, including genetic fingerprinting, immunodetection, and reagentless technologies, that have the necessary sensitivity, specificity, and multiplex capabilities.

Develop improved, cheaper, and accurate RTMSs for routine water quality measurements.

Examine the use of nonspecific detection technologies for RTMSs.

Develop data fusion approaches for RTMSs that can minimize false positives.

Develop and test new monitoring technologies suitable for wastewater security applications.

Improve syndromic surveillance tools and develop a health surveillance network with appropriate linkages to water quality monitoring.

Continue to develop and refine the efficiency of a system-wide laboratory response network, including the development of mobile analysis units.

Continue fundamental research to understand the chemical and biological reactions that affect the fate and transport of contaminants in distribution systems to verify the constants used in MS-EPANET and TEVA.

Include alternative approaches to uncertainty design (e.g., fuzzy logic, Bayesian Maximum Entropy) in the TEVA model that are based more strongly upon stochastic than deterministic principles given that many of the input parameters to the current TEVA model are highly uncertain.

Develop projects for training water utilities in the value and use of EPANET, MS-EPANET, and TEVA.

Some of these research priorities may be more appropriately accomplished by universities, companies, or other agencies that have the necessary expertise, resources, and funding to successfully complete these tasks. The development of multiplex detection protocols and portable, field-deployable platforms are examples of tasks that might be better managed by some group other than the EPA. Work to determine the sensitivity and specificity of designated protocols for different biothreat agents could be conducted by university laboratories or private industry, with collaborative input from the EPA, considering their understanding of the needs of the water sector. Utilization of research resources outside the EPA would expand the variety of emerging, innovative analytical technologies that might be used to support the EPA’s efforts in enhancing the nation’s water security.

RESEARCH RECOMMENDATIONS: IMPROVED RESPONSE AND RECOVERY

Recommendations are provided in this section for future research that should improve response and recovery after a water security incident. Research suggestions related to tools and data for emergency planning and response, contingencies, risk communication and behavioral sciences, decontamination, and lessons learned from natural disasters are presented below.

Tools and Data for Emergency Planning and Response

Continued development of emergency response databases.

The EPA released preliminary versions of the Water Contamination Information Tool (WCIT) and the Consequence Assessment Tool (CAT) to provide data on contaminant properties, toxicity, and exposure threats (see Chapter 4 ), but the databases are still in their infancy, and numerous data gaps exist. The EPA will need to prioritize its continued efforts to further develop these response databases. Therefore, the EPA should develop strategic plans for WCIT and CAT, outlining the long-term goals for the databases and addressing questions such as:

What stakeholders will be served by the databases?

What categories of information do these stakeholders need?

How many contaminants should be included?

What linkages to other databases should be established?

The EPA will need to determine criteria for prioritizing what contaminants are added to the database and how to maintain and update the information. If WCIT and CAT are not continually revised to incorporate the latest scientific knowledge, the databases will become outdated. Expanding or even maintaining a database requires considerable resources, both intellectual and financial. If a commitment is not made initially for the necessary resources to update and maintain a database, spending the resources to create it becomes debatable. The EPA is currently facing similar issues maintaining its Integrated Risk Information System (IRIS) database.

The EPA should also clearly define the data quality objectives for WCIT/CAT and incorporate peer review of the data, as necessary, to meet these objectives. For example, the EPA may decide that some information about a contaminant is better than none, even if that information has limitations. This is a legitimate approach; however, the EPA should provide a mechanism that helps to ensure that individuals using the databases understand the data quality and their limitations. One mechanism for accomplishing this would be to add quality notations for each datum. Regardless of the approach taken, the EPA needs to describe the extent to which the data have been reviewed.

Evaluation and Improvement of Tools and Databases

With the forthcoming completion of at least the first stages of many tools and databases (e.g., WCIT, CAT), the EPA should consider the evaluation/improvement cycle. This will require the development of procedures to evaluate the utility and usability of these tools by potential constituencies. In addition, the EPA should take advantage of the tests afforded in response to “real-life” incidents. For example, some of the tools and databases were used (albeit in an early stage of their development) in the response to Hurricane Katrina. A formal assessment of knowledge gained from this experience could assist in the improvement and development of the tools.

Filling Data Gaps

The state of knowledge of the health risks from water contaminants that could be used in a malicious event is quite limited, as shown by the limited number of chemicals and even fewer biologicals in the WCIT/CAT databases and the many blank data fields in these databases. Important experimental and computational research is under way at the EPA to address some of these data gaps (see Chapter 4 , Section 3.6), but many gaps remain. There are two applications of toxicity/infectivity information that would be useful to the EPA for response and recovery efforts. The first is development of guidance for dissolved concentrations that would pose an immediate acute risk to exposed individuals, analogous to the inhalation immediate danger to life and health values of the National Institute for Occupational Safety and Health. The EPA is currently working on this problem by developing a database on acute and

chronic health effects associated with priority contaminants, although much work remains to be done. The second is guidance for determining the appropriate “acceptable” level remaining after cleanup/decontamination. This second aspect has not yet been strongly emphasized in the EPA research program. It is recommended that the EPA convene a working group to develop research and prioritization strategies for filling these data gaps and for ascertaining current gaps in knowledge with respect to rapid estimation of toxicity/infectivity in the absence of specific experimental information. Decisions for setting priorities for the data gathering efforts should be made with full consideration of dual-use benefits.

Contingencies for Water System Emergencies

Further study of water supply alternatives should be a high priority, considering their pivotal role in response and recovery and their dual-use applications for natural disasters or system failures. However, the subject of water supply contingencies seems to have been given a low priority in the EPA’s research program to date. Completion of the work in progress should be the first priority. The committee debated the value of investing significant resources in developing technologies that could supply drinking water for large communities over long-term disruptions because of the rarity of the need for such technologies. Nevertheless, the EPA should draw upon the research and development efforts of the Department of Defense in this area and work to test the application of these technologies to water security scenarios.

The EPA should consider including new research on contingencies for failures of the human subsystem in water system security. Such research could examine current practices for identifying back-up operators in the case of widespread incapacitation in both short-term and long-term scenarios. This research could also identify best practices, which could be incorporated into EPA guidance to water utilities for their emergency response planning.

Preliminary research suggests that geographic information systems (GIS) could be of significant value to utilities for identifying contingencies in the event of system failures. Therefore, further efforts may be needed to inform utilities about the value of GIS for emergency response and provide guidance for integrating GIS into their emergency planning procedures. National geodata standards may be needed to promote consistency and facilitate data exchange among users.

Behavioral Sciences and Risk Communication

The National Homeland Security Research Center (NHSRC) has made substantial progress in the development of risk communication guidance and training (see Chapter 4 ), but very little emphasis has been devoted to research on understanding how the public may respond to risk communication messages and how to improve communication of risks to the public. Terrorism presents risks that are new, evolving, and difficult to characterize; thus, water security poses communication challenges that should be addressed using scientifically rigorous research in the fields of risk communication and behavioral sciences. The EPA should continually reassess the role risk communication has in its overall risk management framework and fully integrate risk communication efforts into the overall risk management program. Behavioral science and associated risk communication research should be a high priority in the EPA’s future water security research plans. The following recommendations are targeted toward water-security events, but the proposed research has dual benefits for improving non-security-related communications with the public.

Analysis of Factors that Build Trust and Improve Communication

Research and experience prove that one of the most important keys to communication success is an organization’s ability to establish, maintain, and increase trust and credibility with key stakeholders, including employees, regulatory agencies, citizen groups, the public, and the media. To improve overall communication strategies in a water-related emergency, research is needed that analyzes factors that build trust and reduce fear (e.g., What types of concerns do people have related to public health emergencies, water security issues, or bioterrorism? How do utilities build trust and credibility with the public around water security incidents?). In addition, research is needed to analyze methods to counter and reduce the possibility of misinformation or false information being distributed to the public and key stakeholders.

Understanding Institutional Behavior

Building response and recovery capacity requires agencies that might be involved in a water security event to develop stronger working relationships. Although water utilities, public health agencies, law enforcement, emergency responders, and the media do not have a long history of collaborating and working together, several state drinking water programs have taken the lead in carrying out tabletop exercises as well as on-the-ground exercises to address this issue. These state programs have also undertaken measures to facilitate an understanding of the roles and responsibilities of the various potential players, including federal, state, and local law enforcement; state and local health agencies; state and local emergency response agencies; and water utilities. The EPA could glean useful information from these ongoing state and local activities. Nevertheless, additional research is needed to better understand the culture of the agencies that will be responding to events, how these agencies will interact in a water-related crisis, and what level of effort is needed to maintain collaboration in planning and preparedness. This research could identify barriers to more effective collaboration, and these findings could be used to create training scenarios that could improve coordination and resolve potential conflicts in advance. This research is a short-term priority given the importance of coordinated interaction during a crisis. The research could be performed relatively quickly because there is a wealth of experiences, particularly at the state level, related to agency interactions in water-related crises.

Investigate Applicability of Research in Behavioral Science

While some of the recommended research on risk communication and behavioral science may need to be managed by the EPA to address specific water security-related issues, the EPA should also take advantage of other behavioral science research currently being conducted through university-based partnerships, including those established by the Homeland Security Centers of Excellence program. For example, the University of Maryland’s National Consortium for the Study of Terrorism and Responses to Terror (START) is conducting original research on issues that are poorly understood, including risk perception and communication, household and community preparedness for terrorist attacks, likely behavioral responses by the public, social and psychological vulnerability to terrorism, and strategies for mitigating negative psychologi-

cal effects and enhancing resilience in the face of the terror threat. The START center is also synthesizing existing research findings in order to provide timely guidance for decision makers and the public, paying special attention to how diverse audiences react to and are affected by threats and preparedness efforts.

In addition, the CDC has developed a national network of 50 Centers for Public Health Preparedness (CPHP) to train the public health workforce to respond to threats to our nation's health, including bioterrorism. These centers work to strengthen terrorism preparedness and emergency public health response at the state and local level and to develop a network of academic-based programs contributing to national terrorism preparedness and emergency response capacity. Information from the CPHP may be relevant and useful to the water sector.

Pretesting Risk Communication Messages

Although the message mapping workshops are a good start to assist stakeholders in preparing messages that will be relevant in a water security incident, the messages have not been tested and evaluated. Therefore, the EPA should engage the research community in pretesting messages being developed by the Center for Risk Communication so that case studies and scenarios can be analyzed for effectiveness in reaching key audiences, and problems can be corrected in advance. Sophisticated evaluation techniques and standard research procedures are used by the CDC to pretest public messages. This evaluation research should be based on standard criteria established in the risk communication literature (e.g., Mailback and Parrott, 1995; National Cancer Institute, 2002; Witte et al., 2001).

Analysis of the Risks and Benefits of Releasing Security Information

The decision of when to release or withhold water security information is critical to the development of a risk communication strategy. Therefore, the EPA should analyze the risks and benefits of releasing water security information, considering input from its broad range of constituents, and develop transparent agency guidance on when to release information versus when to withhold it due to security concerns.

The committee considers this a priority because of the difficulty and importance of the information sharing problem.

Water-Related Risk Communication Training

As the lead U.S. agency in water system security, the EPA should assume the responsibility for developing a national training program on water-related risk communication planning and implementation for water managers. This should be done in collaboration with the water and wastewater organizations, state government agencies, public health officials, health care officials, and others engaged in communication of risks during water-related emergencies.

Decontamination

Decontamination research is critical to improving response and recovery, and the products are applicable to address unintentional contamination events from natural disasters (e.g., hurricanes, floods, earthquakes) and routine malfunctions (e.g., pipe breaks, negative pressures due to power losses). The EPA has numerous ongoing projects in this area that should be completed, but additional research topics are also suggested below.

Addressing Data Gaps

EPA decontamination research products released thus far have shown that fundamental physical, chemical, and/or biological characteristics of many threat agents of concern are not yet known. Therefore, additional laboratory research is needed related to the behavior of contaminants in water supply and wastewater systems and methods for decontaminating water infrastructure. For example, one research priority would be to develop inactivation rate data for all microbes of concern with both free and combined chlorine strategies, because both approaches are used in the water industry. Rate and equilibrium data for adsorption/desorption of contaminants on pipe walls is also needed, although the EPA could also take advantage of existing databases on structure-activity relationships to predict these behaviors. Long-term re-

search, perhaps in partnership with other Office of Research and Development units, could enhance our understanding of the fate, transport, and transformation of toxics in water and wastewater environments.

Decontamination Strategies

The EPA should build on its ongoing work in the area of decontamination and address gaps in the current knowledge base. For example, research is needed to examine readily available household inactivation methods for biological agents (including spore-formers), such as microwaving. The EPA should also work to further the development of innovative decontamination technologies that address important water security concerns. Research and development on new POU/POE technologies, such as superheated water devices, could help overcome operational disadvantages of the products currently on the market.

Prioritizing Future Surrogate Research

Surrogates are relevant to numerous water security research applications, including research on contaminant fate and transport, human exposure risks, and decontamination. Research is ongoing to identify surrogates or simulants for biological agents, to determine which surrogates are appropriate, and to determine the ability of typical drinking water disinfection practices (chlorination and chloramination) to inactivate those agents (see Chapter 4 , Section 3.2). Much of the research has focused on Bacillus anthracis and other bacterial agents, but the EPA should determine if surrogates for research on biotoxins and viruses are needed and whether additional surrogates are needed for other bacterial agents. A viral simulant or surrogate would be helpful to examine virus survival in fresh water, drinking water, and sewage, as well as virus susceptibility to water disinfectants. Research in this area has relevance to viral bioterrorism agents and also has strong dual-use research applications because viral surrogates could facilitate risk assessment studies on natural viruses (e.g., SARS, avian influenza).

Surrogate research is a laborious experimental process (see Box 4-1 ) that must be conducted in one of the few laboratories already authorized to keep and work with select agents. Considerable research is required to compare the select agent with candidate surrogates under the experimental conditions of interest. As discussed in Chapter 4 , surrogates need not

mimic in all respects the agents they stand in for. For some important security or decontamination uses, it may only be necessary that they provide an appropriate bound on the characteristic of interest in the target agent (e.g., persistence, disinfectant sensitivity). Therefore, the EPA should carefully consider and prioritize the agents and the research applications for which surrogates are needed. The prioritization process for surrogates should consider the following:

Which types of research could be greatly facilitated through the availability of surrogates?

Which types of research with surrogates might have “dual-use” applications (i.e., could the properties of certain surrogates also be usefully extrapolated to other common organisms)?

Which types of research should be done only with select agents?

How closely should the surrogate properties of interest match that of the target organism?

What are the costs and benefits to the research program associated with surrogate development versus use of the pathogenic agents?

The EPA should engage a limited number of individuals (e.g., federal partners, academics) who are involved in similar research in this prioritization process.

Lessons Learned from Natural Disasters

Midway through the committee’s work, NRC (2005; see Appendix A ) suggested the EPA take advantage of experience gained in the aftermath of Katrina so as to improve future response and recovery efforts for water security. While a hurricane caused this catastrophe, it is conceivable that a similar result might have occurred if the levees had been destroyed by terrorist explosives. Thus, New Orleans offered a living laboratory to study many aspects of the impacts of a disaster on water and wastewater systems of all sizes. Failure modes, infrastructure interdependencies, decontamination and service restoration strategies, the availability of alternative supplies, communication strategies, and the ability to service special institutions (e.g., hospitals) and special needs individuals could all have been examined in the immediate aftermath of the hurricane. To the best of the committee’s knowledge, however, the EPA has not attempted to compile a knowledge base from this experience. As

time passes, it will become increasingly difficult to reconstruct what transpired. Other natural or manmade disasters, such as the earthquakes in California in 1989 and 1994 or the “Great Flood of 1993” in the Mid-west, or natural contamination events, such as the Milwaukee C ryptosporidium outbreak, may also offer opportunities to mine important data about the failure or recovery of water and wastewater systems, but detailed information on these earlier occurrences may be lacking. In the future, the NHSRC should be poised to seize opportunities for learning about response and recovery after major natural or man-made disasters affecting water or wastewater systems.

Summary of Research Priorities for Improving Response and Recovery

Determine strategic plans for managing and maintaining the WCIT/CAT databases, considering the likely uses and long-term goals for the databases.

Develop and implement a strategy for evaluating the utility and usability of the response tools and databases, including stakeholder feedback and lessons learned during their use under “real-life” incidents.

Convene a working group to develop research strategies for filling the data gaps in WCIT/CAT and other planned emergency response databases.

Contingencies for Water Emergencies

Complete the work in progress on contingencies and infrastructure interdependencies under Section 3.5 of the Action Plan.

Test and evaluate the most promising innovative water supply technologies that enable or enhance the short- or long-term delivery of drinking water in the event of systemic failure of water systems. Analyze the positive features and those areas needing improvement prior to full-scale deployment.

Conduct research on potential contingencies for failures of the “human subsystem.”

Analyze factors that build trust, reduce fear, and prevent panic to improve overall communication strategies in a water-related emergency.

Investigate the behavioral science research being conducted by the Homeland Security University Centers of Excellence and other federal agencies for applicability to the water sector.

Pretest messages being developed by the Center for Risk Communication and analyze case studies and scenarios for effectiveness.

Analyze the risks and benefits of releasing security information to inform the EPA’s risk communication strategies and its practices on information sharing.

Fully integrate risk communication efforts into the overall risk management program and provide adequate resources that ensure these efforts remain a high priority in the EPA’s future water security research program.

Conduct research to better understand how agencies will interact in a water-related crisis situation and determine what strategies will be most effective in encouraging and maintaining collaboration in planning and preparedness.

Complete the many decontamination projects in progress under Section 3.4 of the Action Plan.

Develop predictive models or laboratory data for inactivation of bioterrorism agents in both free chlorine and chloramines that can be used in MS-EPANET and the TEVA model.

Explore development and testing of new POU/POE devices that may overcome the disadvantages of existing devices.

Examine readily available household inactivation methods for biological agents (including spore-forming agents), such as microwaving.

Determine the costs and benefits of further research to identify additional surrogates, considering which agents under which conditions or applications should be prioritized for surrogate development research.

Use the remaining data from the experience of Hurricane Katrina to analyze the optimal response and recovery techniques (e.g., water supply alternatives, contingency planning, and infrastructure interdependencies) that would also apply to water security events.

Integrate experience with decontamination of the distribution system in New Orleans after Hurricane Katrina to improve EPA guidance for water security decontamination.

Evaluate risk communication strategies related to Hurricane Katrina or other past disaster events to determine if communication strategies related to drinking water safety reached the most vulnerable populations.

Develop a post-event strategy for learning from future natural disasters affecting water systems. This strategy should support on-site assessments of impacts and interdependencies and evaluations of successes and failures during response and recovery.

Continue to develop and maintain the WCIT/CAT databases according to the objectives set forth in the strategic database management plan. Incorporate a mechanism to provide on-going peer review of the data to meet its data quality objectives.

Continue experimental and computational research to fill critical data gaps in WCIT/CAT, including research on the health effects of both acute and chronic exposure to priority contaminants.

Develop new, innovative technologies for supplying drinking water to affected customers over both short- and long-term water system failures.

Risk Communication and Behavioral Sciences

Develop a program of interdisciplinary empirical research in behavioral sciences to better understand how to prepare stakeholders for water security incidents. The EPA should support original research that will help address critical knowledge gaps. For example:

What are the public’s beliefs, opinions, and knowledge about water security risks?

How do risk perception and other psychological factors affect responses to water-related events?

How can these risks be communicated more effectively to the public?

Develop a national training program on water-related risk communication planning and implementation for water managers.

Continue laboratory research to fill the data gaps related to behavior of contaminants in water supply and wastewater systems and methods for decontaminating water infrastructure.

Continue surrogate research based on the research prioritization determined in collaboration with an interagency working group. The EPA should also explore ways that this surrogate research could assist in responding to everyday agents or to other routes of exposure (e.g., inhalation, inactivating agents on surfaces).

The EPA has historically been a lead federal agency in understanding the fate and transport of contaminants in the environment and has a clear understanding of the practical concerns of the water sector. Thus, the EPA remains the appropriate lead agency to develop the tools for emergency response and to prioritize the research needed to fill the remaining gaps, with input from key stakeholders. The EPA is also well suited to develop a national training program on water-related risk communication and to evaluate lessons learned from Hurricane Katrina and other past disaster events. However, innovative technology development research, such as the development of novel technologies for supplying water during system failures, should be conducted by other agencies,

university researchers, or firms with the greatest expertise. The EPA, instead, should focus its efforts on harvesting information on existing technologies, synthesizing this information for end users, and providing guidance to developers on unique technology needs for water security. Behavioral science research and evaluation research is more appropriately conducted by universities or other federal agencies (e.g., CDC) that have the necessary expertise to complete these tasks. However, the EPA still needs in-house behavioral science experts able to supervise and use this work to best advantage.

CONCLUSIONS AND RECOMMENDATIONS

In this chapter, recommendations are provided for future research directions in the area of water security. Two key water security research gaps—behavioral science and innovative future system design—that were not considered in the short-term planning horizon of the Action Plan are identified. In accordance with the committee’s charge (see Chapter 1 ), short- and long-term water security research priorities are presented in three areas: (1) developing products to support more resilient design and operation of facilities and systems, (2) improving the ability of operators and responders to detect and assess incidents, and (3) improving response and recovery.

The EPA should develop a program of interdisciplinary empiri cal research in behavioral science to better understand how to pre pare stakeholders for water security incidents. The risks of terrorism are dynamic and uncertain and involve complex behavioral phenomena. The EPA should take advantage of existing behavioral science research that could be applied to water security issues to improve response and recovery efforts. At the same time, when gaps exist, the EPA should support rigorous empirical research that will help address, for example, what the public’s beliefs, opinions, and knowledge about water security risks are; how risk perception and other psychological factors affect responses to water-related events; and how to communicate these risks effectively to the public.

The EPA should take a leadership role in providing guidance for the planning, design, and implementation of new, more sustainable and resilient water and wastewater facilities for the 21st century. Given the investments necessary to upgrade and sustain the country’s water and wastewater systems, research on innovative approaches to make the infrastructure more sustainable and resilient both to routine and

malicious incidents would provide substantial dual-use benefits. The EPA should help develop and test new concepts, technologies, and management structures for water and wastewater utilities to meet objectives of public health, sustainability, cost-effectiveness, and homeland security. Specific research topics related to drinking water and wastewater, such as decentralized systems and in-pipe interventions to reduce exposure from contaminants, are suggested.

Recommended research topics in the area of supporting more resilient design and operation of drinking water and wastewater systems include improved processes for threat and consequence assessments and innovative designs for water and wastewater. A thorough and balanced threat assessment encompassing physical, cyber, and contaminant threats is lacking. To date, the EPA has focused its threat assessments on contaminant threats, but physical and cyber threats deserve more attention and analysis because this information could influence the EPA’s future research priorities and utilities’ preparedness and response planning.

Research suggestions that improve the ability of operators and responders to detect and assess incidents build upon the EPA’s current research in the areas of analytical methodologies and monitoring and distribution system modeling. In the short term, the EPA should continue research to develop and refine a first-stage RTMS based on routine water quality parameters with dual-use applications. Long-term research recommendations include the development of innovative detection technologies and cheaper, more accurate RTMSs. To support the simulation models in development, a substantial amount of fundamental research is needed to improve understanding of the fate and transport of contaminants in distribution systems. Based on the number of emerging technologies and agents of interest, the EPA should develop a prioritization strategy for technology testing to optimize the resources devoted to this effort.

Recommendations for future research priorities to improve response and recovery emphasize the sustainability of tools for emergency planning and response (e.g., WCIT/CAT) and improving research on water security contingencies, behavioral sciences, and risk communication. The EPA should also evaluate the relative importance of future laboratory work on surrogate development and address data gaps in the knowledge of decontamination processes and behavior. So far, the EPA has not taken advantage of the many opportunities from Hurricane Katrina to harvest lessons learned related to response and recovery, and the window of opportunity is rapidly closing.

Some of the research recommendations provided in this chapter lie outside of the EPA’s traditional areas of expertise. The EPA will need to consider how best to balance intramural and extramural research funding to carry out this research, while maintaining appropriate oversight and input into the research activities. Increasing staff expertise in some key areas, such as physical security and behavioral sciences, will be necessary to build a strong and well-rounded water security research program.

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Concern over terrorist attacks since 2001 has directed attention to potential vulnerabilities of the nation's water and wastewater systems. The Environmental Protection Agency (EPA), which leads federal efforts to protect the water sector, initiated a research program in 2002 to address immediate research and technical support needs. This report, conducted at EPA's request, evaluates research progress and provides a long-term vision for EPA's research program. The report recommends that EPA develop a strategic research plan, address gaps in expertise among EPA program managers and researchers, and improve its approaches to information dissemination. The report recommends several high-priority research topics for EPA, including conducting empirical research in behavioral science to better understand how to prepare people for water security incidents.

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• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• Limitations of the Study
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
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The limitations of the study are those characteristics of design or methodology that impacted or influenced the interpretation of the findings from your research. Study limitations are the constraints placed on the ability to generalize from the results, to further describe applications to practice, and/or related to the utility of findings that are the result of the ways in which you initially chose to design the study or the method used to establish internal and external validity or the result of unanticipated challenges that emerged during the study.

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67; Theofanidis, Dimitrios and Antigoni Fountouki. "Limitations and Delimitations in the Research Process." Perioperative Nursing 7 (September-December 2018): 155-163. .

Importance of...

Always acknowledge a study's limitations. It is far better that you identify and acknowledge your study’s limitations than to have them pointed out by your professor and have your grade lowered because you appeared to have ignored them or didn't realize they existed.

Keep in mind that acknowledgment of a study's limitations is an opportunity to make suggestions for further research. If you do connect your study's limitations to suggestions for further research, be sure to explain the ways in which these unanswered questions may become more focused because of your study.

Acknowledgment of a study's limitations also provides you with opportunities to demonstrate that you have thought critically about the research problem, understood the relevant literature published about it, and correctly assessed the methods chosen for studying the problem. A key objective of the research process is not only discovering new knowledge but also to confront assumptions and explore what we don't know.

Claiming limitations is a subjective process because you must evaluate the impact of those limitations . Don't just list key weaknesses and the magnitude of a study's limitations. To do so diminishes the validity of your research because it leaves the reader wondering whether, or in what ways, limitation(s) in your study may have impacted the results and conclusions. Limitations require a critical, overall appraisal and interpretation of their impact. You should answer the question: do these problems with errors, methods, validity, etc. eventually matter and, if so, to what extent?

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67; Structure: How to Structure the Research Limitations Section of Your Dissertation. Dissertations and Theses: An Online Textbook. Laerd.com.

Descriptions of Possible Limitations

All studies have limitations . However, it is important that you restrict your discussion to limitations related to the research problem under investigation. For example, if a meta-analysis of existing literature is not a stated purpose of your research, it should not be discussed as a limitation. Do not apologize for not addressing issues that you did not promise to investigate in the introduction of your paper.

Here are examples of limitations related to methodology and the research process you may need to describe and discuss how they possibly impacted your results. Note that descriptions of limitations should be stated in the past tense because they were discovered after you completed your research.

Possible Methodological Limitations

• Sample size -- the number of the units of analysis you use in your study is dictated by the type of research problem you are investigating. Note that, if your sample size is too small, it will be difficult to find significant relationships from the data, as statistical tests normally require a larger sample size to ensure a representative distribution of the population and to be considered representative of groups of people to whom results will be generalized or transferred. Note that sample size is generally less relevant in qualitative research if explained in the context of the research problem.
• Lack of available and/or reliable data -- a lack of data or of reliable data will likely require you to limit the scope of your analysis, the size of your sample, or it can be a significant obstacle in finding a trend and a meaningful relationship. You need to not only describe these limitations but provide cogent reasons why you believe data is missing or is unreliable. However, don’t just throw up your hands in frustration; use this as an opportunity to describe a need for future research based on designing a different method for gathering data.
• Lack of prior research studies on the topic -- citing prior research studies forms the basis of your literature review and helps lay a foundation for understanding the research problem you are investigating. Depending on the currency or scope of your research topic, there may be little, if any, prior research on your topic. Before assuming this to be true, though, consult with a librarian! In cases when a librarian has confirmed that there is little or no prior research, you may be required to develop an entirely new research typology [for example, using an exploratory rather than an explanatory research design ]. Note again that discovering a limitation can serve as an important opportunity to identify new gaps in the literature and to describe the need for further research.
• Measure used to collect the data -- sometimes it is the case that, after completing your interpretation of the findings, you discover that the way in which you gathered data inhibited your ability to conduct a thorough analysis of the results. For example, you regret not including a specific question in a survey that, in retrospect, could have helped address a particular issue that emerged later in the study. Acknowledge the deficiency by stating a need for future researchers to revise the specific method for gathering data.
• Self-reported data -- whether you are relying on pre-existing data or you are conducting a qualitative research study and gathering the data yourself, self-reported data is limited by the fact that it rarely can be independently verified. In other words, you have to the accuracy of what people say, whether in interviews, focus groups, or on questionnaires, at face value. However, self-reported data can contain several potential sources of bias that you should be alert to and note as limitations. These biases become apparent if they are incongruent with data from other sources. These are: (1) selective memory [remembering or not remembering experiences or events that occurred at some point in the past]; (2) telescoping [recalling events that occurred at one time as if they occurred at another time]; (3) attribution [the act of attributing positive events and outcomes to one's own agency, but attributing negative events and outcomes to external forces]; and, (4) exaggeration [the act of representing outcomes or embellishing events as more significant than is actually suggested from other data].

Possible Limitations of the Researcher

• Access -- if your study depends on having access to people, organizations, data, or documents and, for whatever reason, access is denied or limited in some way, the reasons for this needs to be described. Also, include an explanation why being denied or limited access did not prevent you from following through on your study.
• Longitudinal effects -- unlike your professor, who can literally devote years [even a lifetime] to studying a single topic, the time available to investigate a research problem and to measure change or stability over time is constrained by the due date of your assignment. Be sure to choose a research problem that does not require an excessive amount of time to complete the literature review, apply the methodology, and gather and interpret the results. If you're unsure whether you can complete your research within the confines of the assignment's due date, talk to your professor.
• Cultural and other type of bias -- we all have biases, whether we are conscience of them or not. Bias is when a person, place, event, or thing is viewed or shown in a consistently inaccurate way. Bias is usually negative, though one can have a positive bias as well, especially if that bias reflects your reliance on research that only support your hypothesis. When proof-reading your paper, be especially critical in reviewing how you have stated a problem, selected the data to be studied, what may have been omitted, the manner in which you have ordered events, people, or places, how you have chosen to represent a person, place, or thing, to name a phenomenon, or to use possible words with a positive or negative connotation. NOTE :   If you detect bias in prior research, it must be acknowledged and you should explain what measures were taken to avoid perpetuating that bias. For example, if a previous study only used boys to examine how music education supports effective math skills, describe how your research expands the study to include girls.
• Fluency in a language -- if your research focuses , for example, on measuring the perceived value of after-school tutoring among Mexican-American ESL [English as a Second Language] students and you are not fluent in Spanish, you are limited in being able to read and interpret Spanish language research studies on the topic or to speak with these students in their primary language. This deficiency should be acknowledged.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Senunyeme, Emmanuel K. Business Research Methods. Powerpoint Presentation. Regent University of Science and Technology; ter Riet, Gerben et al. “All That Glitters Isn't Gold: A Survey on Acknowledgment of Limitations in Biomedical Studies.” PLOS One 8 (November 2013): 1-6.

Structure and Writing Style

Information about the limitations of your study are generally placed either at the beginning of the discussion section of your paper so the reader knows and understands the limitations before reading the rest of your analysis of the findings, or, the limitations are outlined at the conclusion of the discussion section as an acknowledgement of the need for further study. Statements about a study's limitations should not be buried in the body [middle] of the discussion section unless a limitation is specific to something covered in that part of the paper. If this is the case, though, the limitation should be reiterated at the conclusion of the section.

If you determine that your study is seriously flawed due to important limitations , such as, an inability to acquire critical data, consider reframing it as an exploratory study intended to lay the groundwork for a more complete research study in the future. Be sure, though, to specifically explain the ways that these flaws can be successfully overcome in a new study.

But, do not use this as an excuse for not developing a thorough research paper! Review the tab in this guide for developing a research topic . If serious limitations exist, it generally indicates a likelihood that your research problem is too narrowly defined or that the issue or event under study is too recent and, thus, very little research has been written about it. If serious limitations do emerge, consult with your professor about possible ways to overcome them or how to revise your study.

When discussing the limitations of your research, be sure to:

• Describe each limitation in detailed but concise terms;
• Explain why each limitation exists;
• Provide the reasons why each limitation could not be overcome using the method(s) chosen to acquire or gather the data [cite to other studies that had similar problems when possible];
• Assess the impact of each limitation in relation to the overall findings and conclusions of your study; and,
• If appropriate, describe how these limitations could point to the need for further research.

Remember that the method you chose may be the source of a significant limitation that has emerged during your interpretation of the results [for example, you didn't interview a group of people that you later wish you had]. If this is the case, don't panic. Acknowledge it, and explain how applying a different or more robust methodology might address the research problem more effectively in a future study. A underlying goal of scholarly research is not only to show what works, but to demonstrate what doesn't work or what needs further clarification.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Ioannidis, John P.A. "Limitations are not Properly Acknowledged in the Scientific Literature." Journal of Clinical Epidemiology 60 (2007): 324-329; Pasek, Josh. Writing the Empirical Social Science Research Paper: A Guide for the Perplexed. January 24, 2012. Academia.edu; Structure: How to Structure the Research Limitations Section of Your Dissertation. Dissertations and Theses: An Online Textbook. Laerd.com; What Is an Academic Paper? Institute for Writing Rhetoric. Dartmouth College; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University.

Writing Tip

Don't Inflate the Importance of Your Findings!

After all the hard work and long hours devoted to writing your research paper, it is easy to get carried away with attributing unwarranted importance to what you’ve done. We all want our academic work to be viewed as excellent and worthy of a good grade, but it is important that you understand and openly acknowledge the limitations of your study. Inflating the importance of your study's findings could be perceived by your readers as an attempt hide its flaws or encourage a biased interpretation of the results. A small measure of humility goes a long way!

Another Writing Tip

Negative Results are Not a Limitation!

Negative evidence refers to findings that unexpectedly challenge rather than support your hypothesis. If you didn't get the results you anticipated, it may mean your hypothesis was incorrect and needs to be reformulated. Or, perhaps you have stumbled onto something unexpected that warrants further study. Moreover, the absence of an effect may be very telling in many situations, particularly in experimental research designs. In any case, your results may very well be of importance to others even though they did not support your hypothesis. Do not fall into the trap of thinking that results contrary to what you expected is a limitation to your study. If you carried out the research well, they are simply your results and only require additional interpretation.

Lewis, George H. and Jonathan F. Lewis. “The Dog in the Night-Time: Negative Evidence in Social Research.” The British Journal of Sociology 31 (December 1980): 544-558.

Yet Another Writing Tip

Sample Size Limitations in Qualitative Research

Sample sizes are typically smaller in qualitative research because, as the study goes on, acquiring more data does not necessarily lead to more information. This is because one occurrence of a piece of data, or a code, is all that is necessary to ensure that it becomes part of the analysis framework. However, it remains true that sample sizes that are too small cannot adequately support claims of having achieved valid conclusions and sample sizes that are too large do not permit the deep, naturalistic, and inductive analysis that defines qualitative inquiry. Determining adequate sample size in qualitative research is ultimately a matter of judgment and experience in evaluating the quality of the information collected against the uses to which it will be applied and the particular research method and purposeful sampling strategy employed. If the sample size is found to be a limitation, it may reflect your judgment about the methodological technique chosen [e.g., single life history study versus focus group interviews] rather than the number of respondents used.

Boddy, Clive Roland. "Sample Size for Qualitative Research." Qualitative Market Research: An International Journal 19 (2016): 426-432; Huberman, A. Michael and Matthew B. Miles. "Data Management and Analysis Methods." In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 428-444; Blaikie, Norman. "Confounding Issues Related to Determining Sample Size in Qualitative Research." International Journal of Social Research Methodology 21 (2018): 635-641; Oppong, Steward Harrison. "The Problem of Sampling in qualitative Research." Asian Journal of Management Sciences and Education 2 (2013): 202-210.

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How to write the part scope for further research?

The part scope for further research is essential in every academic study such as a thesis , dissertation or journal paper . The main purpose of this part is to make the readers aware of the findings emerging from the study, and its shortcomings. The shortcomings of the research gap guide future researchers on a domain that they must consider to save time and avoid repetitive outcomes.

Furthermore, this section also gives guidelines to researchers on other dimensions and critical estimations from which the topic can be explored.

Emphasize the significance of further research

There are no specific rules or guidelines for this part. However, since it is expected to be brief and informative, the following format is recommended.

Start this section by reflecting on the significance of the present study in brief. Answering questions such as:

• Whether the research deviated from its initial objectives?
• What was the original idea behind the research?
• From where was the inspiration drawn?

Answering such questions is important because the reader should connect to the idea of the research.

Limitations of the study

Furthermore, briefly explain the limitations of the study. This step proves significant for scholars who wish to address areas that can enrich the research topic further. The limitations can either be presented separately, in an independent section called “Limitations of the research”, or can be integrated within the future scope. Also, the limitations should be scalable and relatable, i.e. something that other researchers feel can be accomplished under different circumstances. This is also the key to setting recommendations for future studies.

Justify the future scope

Furthermore, provide justifications for the reasons why the mentioned areas have not been covered in the current study. Identify the probable bottlenecks other researchers might encounter while considering future research related to the topic. This will help them formulate an achievable or practically applicable plan for their own research, including the scope, aim and methodology.

Suggestions

Finally, the approach of the researcher becomes more direct. To be specific, some direct research suggestions should be given to other scholars for future studies. Be precise so that the reader is confident to undertake future studies in the suggested areas.

Answering the following questions can help:

• What should be explored by others?
• Why is it worth exploring?
• What can be achieved from it?
• Will the suggested study be relevant five to ten years down the line?
• How does it add to the overall body of the literature?

Types of writing a future scope

There are different types of future research scope, based on the kind of writing, such as:

• The future scope is focused solely on study findings.
• The future scope is focused on the theory or theoretical model misused.
• The future scope from lack of literary support.
• The future scope of geographical outreach.
• The future scope of testing methods and statistics.
• The future scope on the complete redesigning of methodology.

Points to keep in mind

The most important aspect of writing the future scope part is to present it in an affirmative way. As identified in the former section, it is crucial to identify if the limitations are methods-based or researcher based. It should be concise and critical to the field of study. Refrain from using a reference in the scope for the future research part.

Make sure the points discussed remain achievable in a proximal time frame. In addition, make sure that they are in relation to the theoretical development of the study in focus.

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A SCIENCE PROTOTYPE: RUTHERFORD AND THE ATOM

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Conclusions and Suggestions for Further Research

• First Online: 28 July 2018

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De Somer, M. (2019). Conclusions and Suggestions for Further Research. In: Precedents and Judicial Politics in EU Immigration Law. European Administrative Governance. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-93982-7_9

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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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How to Make Research More Relevant to All

Five questions with courtney beard on engaging communities in research..

Courtney Beard , PhD, faced a problem familiar to many Harvard Medical School researchers: How to diversify your research studies to make them more applicable to the general population.

In Beard’s case, she was planning a study in the general population to evaluate a mental health app she developed as a cognitive-behavioral tool for so-called interpretation bias, which studies suggest is an important factor in anxiety and depression. The app was first tested at McLean Hospital, which serves a mostly white, well-educated population. She wanted to make sure her app also worked well for people historically under-represented in research studies, including people who identify as Black, Hispanic, and Latinx.

Serendipitously, Beard learned from a colleague about the study review service offered by the Community Coalition for Equity in Research , and immediately signed up. She filled out a two-page equity-focused template describing her study and made a 10-minute video outlining her research interests. Shortly thereafter, she found herself video-conferencing with a panel of community-embedded experts who provided individualized advice and guidance on how to make her study more equitable.

Beard, a clinical psychologist with expertise in anxiety disorders and cognitive behavior therapy, is associate professor of psychology in the Department of Psychiatry at Harvard Medical School (HMS), and director of the Cognition and Affect Research and Education (CARE) Laboratory at McLean Hospital.

The app you’ve developed, HabitWorks, supports new ways of thinking for people facing mental health problems. How does this fit into the CARE lab?

Much of our work involves identifying mechanisms that keep people anxious or depressed, such as mental habits, and then developing treatments to target those very specific mental habits. Habit Works is a perfect example of that. It focuses on how people interpret the countless ambiguous situations they face throughout the day. We know that interpretation bias plays a big role in how people feel in the moment, and it impacts what they do, especially if they’re feeling anxious.

HabitWorks has been developed and tested over a number of years in people who have lived experience with these conditions. The aim is to help people become more aware of how they’re interpreting situations and consider opening to alternative interpretations. Perhaps they become a little more flexible in their thinking, or at least start to pause when they notice themselves jumping to a particular type of conclusion.

Your second HabitWorks study plan was reviewed by the Community Coalition for Equity in Research in September of 2022. Did your approach change at all as a result of the review?

Yes, it changed substantially. We originally planned to jump right into a pilot study to test our app in a general population and recruit a few hundred people. As a result of the review, we decided to take a step back and do a much smaller study specifically with people who identify as Black, Hispanic, or Latinx. We wanted to understand how they were experiencing the intervention and make sure it was acceptable to them before testing it more broadly, precisely because it had been first developed and tested in the primarily white population served by McLean. At the end of the study, we interviewed participants to clearly understand how they were using and experiencing the app.

“That warm handoff is critical. It has enabled us to be much more successful in getting people to respond to us. Otherwise, I’m just another Harvard professor wanting something from them.”

A particular concern was that the app presents day-to-day situations that are uncertain or ambiguous in some way. For people from minoritized backgrounds, those types of situations may bring up discrimination experiences or questions of identity in addition to the anxiety-related interpretations that are being targeted for reframing. We wanted to be sure the app wasn’t bringing up thoughts about discrimination, causing stress, or creating a perception that we were asking people to reappraise certain types of situations, which could be invalidating and unhelpful.

With changes recommended by the Coalition, we were able to answer many of those questions in advance of the bigger study in a broader population, which we’ve now just started. We found the app itself was easily accepted. People enjoyed using it and it didn’t cause harm. That was very reassuring.

In response to the Coalition’s recommendations, we also expanded and revamped the resources we provide to people along with the app. We added more resources around finding a therapist based on various aspects related to identity, as well as information on topics such as financial supports and coping with discrimination. We now have an exhaustive resource list that we give people.

You’re also working with the new Community Ambassador Initiative on a separate research program that uses the HabitWorks app to tackle parental transference of anxiety. What does that entail?

The community ambassadors have been helping us form connections and spread the word about an NIMH-funded trial that is testing how parents’ interpretation bias might get passed down and ultimately cause anxiety in kids.

Quite a bit of data supports the idea that anxieties are passed down, and parenting behaviors might be even more important than genetics. Some data suggests that how parents interpret threat in their world leads them to engage in parenting behaviors that teach the child that the world is threatening, that maybe they can’t handle it and should avoid it. Those behaviors can keep the parent anxious as well as transfer anxiety to the children.

We’re using the HabitWorks app to manipulate parents’ interpretations and examine the downstream effects on their anxiety and their parenting behaviors related to anxiety. Then we bring in their kids and assess their own interpretations and anxiety.

What were some of the challenges you faced that the community ambassadors have been helping address?

We’re trying to enroll 300 parent-child dyads and would like at least 30% of those to be parents of color, mostly focusing on Black, Hispanic, and Latinx families. We also want fathers to represent 30% of our cohort because they have been largely ignored in this literature so far.

“Everyone’s hopefully realizing that if we want our research to have an impact, community-engaged research is something everyone should be trained in and conducting.”

We’ve been partnering with different organizations in the Springfield area in Western Massachusetts. We’re still early in the process, but we hope to expand the reach of our study beyond the populations of Boston and its affluent suburbs. The goal is to have a representative sample from which we can draw meaningful conclusions for all groups of people.

The people we’re working with are deeply embedded in their communities. They’re very well connected across many different community-based organizations and have helped us identify which might be a good fit for our outreach. When I reach out to these organizations, I can say I’m working with someone they already know.

That warm handoff is critical. It has enabled us to be much more successful in getting people to respond to us. Otherwise, I’m just another Harvard professor wanting something from them. That’s not a good way to start.

Community-engaged research has become such a buzzword. What does it mean to you and what do you think it means to other researchers?

It’s something I wish I had learned about when I was in graduate school. A subset of people have been doing this type of research for a long time, but it was not necessarily viewed as relevant to all researchers. I think that is changing now. Everyone’s hopefully realizing that if we want our research to have an impact, community-engaged research is something everyone should be trained in and conducting.

In my work developing treatments for depression and anxiety, I’ve always included the perspectives of people with lived experience. A patient advisory board helped us develop the app, and we’ve asked people about their experiences. But our community engagement had always been specific to the clinic I was partnering with, whether at McLean or primary care clinics. Working with the Coalition has helped me go even further.

I’m eager to get to know these communities, to learn more from them, and to have them inform our future studies. So far, what we research has always been led by my team and me. I’m eager to realize the next phase of this process, to really listen to what research the community thinks is important to conduct.

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Finding and Reading Journal Articles

• Journal Articles: Why You Use Them

Why are articles so important to research?

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Journal articles are the academic's stock in trade, t he basic means of communicating research findings to an audience of one’s peers. That holds true across the disciplinary spectrum, so no matter where you land as a concentrator, you can expect to rely on them heavily. 

Regardless of the discipline, moreover,  journal articles perform an important knowledge-updating function .

Textbooks and handbooks and manuals will have a secondary function for chemists and physicists and biologists, of course. But in the sciences, articles are the standard and  preferred publication form. 

In the social sciences and humanities , where knowledge develops a little less rapidly or is driven less by issues of time-sensitivity , journal articles and books are more often used together.

Not all important and influential ideas warrant book-length studies, and some inquiry is just better suited to the size and scope and concentrated discussion that the article format offers.

Journal articles sometimes just present the most  appropriate  solution for communicating findings or making a convincing argument.  A 20-page article may perfectly fit a researcher's needs.  Sustaining that argument for 200 pages might be unnecessary -- or impossible.

The quality of a research article and the legitimacy of its findings are verified by other scholars, prior to publication, through a rigorous evaluation method called peer-review . This seal of approval by other scholars doesn't mean that an article is the best, or truest, or last word on a topic. If that were the case, research on lots of things would cease. Peer review simply means other experts believe the methods, the evidence, the conclusions of an article have met important standards of legitimacy, reliability, and intellectual honesty.

Searching the journal literature is part of being a responsible researcher at any level: professor, grad student, concentrator, first-year. Knowing why academic articles matter will help you make good decisions about what you find -- and what you choose to rely on in your work.

Think of journal articles as the way you tap into the ongoing scholarly conversation , as a way of testing the currency of  a finding, analysis, or argumentative position, and a way of bolstering the authority (or plausibility) of explanations you'll offer in the papers and projects you'll complete at Harvard. 

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Teaching Research Skills That Transfer to Future Projects

Exploratory research teaches skills that have lifelong use..

Updated August 1, 2024 | Reviewed by Monica Vilhauer

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This post is the fourth in a series.

When helping students become researchers, the goal is not only to equip students to tackle a current research project but also to ensure the learned skills will stay with them for future endeavors. Students must understand which research staples must be applied under any circumstances (like critically evaluating sources or following ethical guidelines) while maintaining the flexibility to try different approaches and make new connections. Students at Laguna Beach High School (LBHS) are learning to do just that.

In Part I of this series I spoke to Jun Shen, the passionate teacher and ed-tech coordinator who runs LBHS’s Authentic Exploratory Research (AER) program . AER is an independent research course inspired by Palo Alto Unified School District’s Advanced Authentic Research program . The program pairs students with adult mentors (such as LBUSD staff, industry experts, and academics) who assist the teens in researching their big questions in fields of their choice.

Former LBHS student Carter Ghere was the third teenager to give us an account of his experience in AER and the findings that his AER research produced. A benefit to meeting with Ghere was that he has since moved on to projects outside the AER program, such as promoting physical and mental health . The research skills Ghere honed in AER, combined with his passion for his new endeavors, show us how students can learn research skills in a way that has lasting benefits.

Jenny Grant Rankin: What can teachers do to help students research effectively, not only for current projects but also for future research endeavors?

Carter Ghere: Teachers can encourage students to think about minor aspects of the project that greatly influence the thesis rather than just the thesis question itself. When I researched car design and why it varies, I had to consider each factor that could help me build a strong argument. What started as research on cars very quickly turned into research into socioeconomics, societal upbringing, and government involvement in diplomatic events and conflict. Automotive design changed because manufacturers were competing against each other to sell more cars or improve efficiency, but mass appeal is the biggest driving aspect of change, so I had to research what changes mass appeal and where interests originate from. Laterally, researching aspects of influence opens up much research to apply to your projects, instead of searching for the answer most people already know. Teachers can teach their students how to see the hidden influences, draw conclusions themselves to strengthen their arguments, and accelerate the research process. Knowing how to do research effectively carries over a lifetime, making every new learning endeavor exciting for students instead of monotonous.

JGR: What was the most significant thing you learned about conducting research?

CG: Relevance and impact. The biggest thing I learned while I was conducting research was keeping in mind how your study affects the current information already available. It’s easy to research and quote what most people know, but genuinely effective research isn’t commonly known or even thought of; the research is supposed to question the current knowledge to create new knowledge.

JGR: What was the most significant thing you learned about communicating research or other work?

CG: Knowing your audience is the biggest thing I learned about communicating my work. Putting myself in the shoes of someone reading my work helped me curate my research to better explain my findings to someone who may need to learn about my topic or why this is important. The last thing you want your audience to feel is confusion; a clear, simple explanation of your findings helps the reader draw their connections and relate them to what they already know.

JGR: What lessons learned in AER do you find yourself applying in your current efforts to promote mental health?

CG: The research experience I have from AER accelerated the work I’ve done beyond high school. In terms of research and the actual information I give out, I know that what I’m discovering isn’t new, but the personal opinion that I have is, and that’s what AER taught me. The thoughts that I have on the subject matter of lifestyle and self-development have more relevance than just plain information.

Learning through apprenticeship and embracing the guidance of a mentor profoundly expanded my understanding. This experience made me realize the vast opportunities I still have to learn and grow. At AER, I had the chance to engage in research, connect with experts in the field, develop personal convictions that I am passionate about, ensure these ideas resonate with others, and communicate them effectively.

Ghere demonstrates what we want students to be able to do with the knowledge and skills we teach: to remember, apply, and develop them perpetually. Ideally, as in Ghere’s case, students also use their research skills to help others and improve our world. To continue reading, look for Part V .

Jenny Grant Rankin, Ph.D., is a Fulbright Specialist for the U.S. Department of State.

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Suggestions for further research

One single PhD research project is by nature restricted to what can be accomplished in four years time. An important result of such a project is a set of new questions that can be used as ideas for further research, as detailed research always unearths further questions.

One target for additional research is the knowledge component. This thesis showed an attractive approach for improving the data and information handling capacity of BC . Some suggestions have been given on how this approach also makes BC a more knowledge-driven industry. There are however many opportunities for much more detailed research in this area.

Though keeping a constant eye on the needs and uses of Specification s, there hasn't been much attention to the inner details of a Specification . Possible attention areas include the knowledge-intensive links to regulations and laws which are probably worth a couple of years of research. How to handle the differences between the generic properties attached to bcoWeb objects and the probably partly different properties as preferred by the Specification . This thesis showed some technical possibilities for multiple Classification s per Specification : what are the organisational, juridical and practical possibilities or difficulties to bring this to practice and to perhaps take it somewhat further by having different Specification s for different kinds of projects?

Additionally, a Specification can be seen as a model that describes the transformation from design to materialisation for a given project. The traditional (paper based or electronic) Specification will be a representation of this future model, just like the 3 D geometry or 2 D geometry is a representation of an IFC model.

ISO 12006-2 is partially FU -based [ 87 ]. There was no time to investigate the possible connections with bcoWeb 's GARM -like development. 12006-2 is quite formal and well-defined, so looking at both from a likewise well-defined OWL -viewpoint seems worthwhile.

Something that did not receive enough attention is the use of the subclass relation. Are catalog items subclasses or instances of bcoWeb TS s, for instance? For the prototype development, the subclass relation was used (which worked), but much more thought should go into this. Also the suitability of Ontologies for multiple viewpoints should receive more attention. Do you need multiple Ontologies or not?

In this thesis, bcoWeb was only filled with objects directly. There are, however, possibilities to mine catalogs and object trees automatically for data. Catalogs and object trees could have a local set of objects, which might be considered potential candidates for inclusion in the core bcoWeb . There is a lot of research to be done on this terrain. Perhaps revisiting neural networks and fuzzy logic is a worthy research target.

With an initial--and needed--focus on a national bcoWeb , there remains a desire for international cooperation, with many larger projects being international in nature and with many suppliers working internationally. Perhaps these international suppliers can be an important link in connecting various national bcoWeb s. At the least, this is an area that can use further research.

Something that did not receive much attention in this thesis is the coupling between bcoWeb and geometry. Some work was done in eConstruct , demonstrating possibilities. This, too, is a worthwhile research target.

Web services themselves are also a potential research target. How can they be made acceptable? What are the limitations? Are certain areas more suited for web services than others? Can a strength calculation be reliably performed? What is the effect on financing and billing structures?