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How to Write a Research Question: Types and Examples 

The first step in any research project is framing the research question. It can be considered the core of any systematic investigation as the research outcomes are tied to asking the right questions. Thus, this primary interrogation point sets the pace for your research as it helps collect relevant and insightful information that ultimately influences your work.   

Typically, the research question guides the stages of inquiry, analysis, and reporting. Depending on the use of quantifiable or quantitative data, research questions are broadly categorized into quantitative or qualitative research questions. Both types of research questions can be used independently or together, considering the overall focus and objectives of your research.  

What is a research question?

A research question is a clear, focused, concise, and arguable question on which your research and writing are centered. 1 It states various aspects of the study, including the population and variables to be studied and the problem the study addresses. These questions also set the boundaries of the study, ensuring cohesion. 

Designing the research question is a dynamic process where the researcher can change or refine the research question as they review related literature and develop a framework for the study. Depending on the scale of your research, the study can include single or multiple research questions. 

A good research question has the following features: 

• It is relevant to the chosen field of study. 
• The question posed is arguable and open for debate, requiring synthesizing and analysis of ideas. 
• It is focused and concisely framed. 
• A feasible solution is possible within the given practical constraint and timeframe. 

A poorly formulated research question poses several risks. 1   

• Researchers can adopt an erroneous design. 
• It can create confusion and hinder the thought process, including developing a clear protocol.  
• It can jeopardize publication efforts.  
• It causes difficulty in determining the relevance of the study findings.  
• It causes difficulty in whether the study fulfils the inclusion criteria for systematic review and meta-analysis. This creates challenges in determining whether additional studies or data collection is needed to answer the question.  
• Readers may fail to understand the objective of the study. This reduces the likelihood of the study being cited by others. 

Now that you know “What is a research question?”, let’s look at the different types of research questions. 

Types of research questions

Depending on the type of research to be done, research questions can be classified broadly into quantitative, qualitative, or mixed-methods studies. Knowing the type of research helps determine the best type of research question that reflects the direction and epistemological underpinnings of your research. 

The structure and wording of quantitative 2 and qualitative research 3 questions differ significantly. The quantitative study looks at causal relationships, whereas the qualitative study aims at exploring a phenomenon. 

• Quantitative research questions:  
• Seeks to investigate social, familial, or educational experiences or processes in a particular context and/or location.  
• Answers ‘how,’ ‘what,’ or ‘why’ questions. 
• Investigates connections, relations, or comparisons between independent and dependent variables. 

Quantitative research questions can be further categorized into descriptive, comparative, and relationship, as explained in the Table below. 

• Qualitative research questions  

Qualitative research questions are adaptable, non-directional, and more flexible. It concerns broad areas of research or more specific areas of study to discover, explain, or explore a phenomenon. These are further classified as follows: 

• Mixed-methods studies  

Mixed-methods studies use both quantitative and qualitative research questions to answer your research question. Mixed methods provide a complete picture than standalone quantitative or qualitative research, as it integrates the benefits of both methods. Mixed methods research is often used in multidisciplinary settings and complex situational or societal research, especially in the behavioral, health, and social science fields. 

What makes a good research question

A good research question should be clear and focused to guide your research. It should synthesize multiple sources to present your unique argument, and should ideally be something that you are interested in. But avoid questions that can be answered in a few factual statements. The following are the main attributes of a good research question. 

• Specific: The research question should not be a fishing expedition performed in the hopes that some new information will be found that will benefit the researcher. The central research question should work with your research problem to keep your work focused. If using multiple questions, they should all tie back to the central aim. 
• Measurable: The research question must be answerable using quantitative and/or qualitative data or from scholarly sources to develop your research question. If such data is impossible to access, it is better to rethink your question. 
• Attainable: Ensure you have enough time and resources to do all research required to answer your question. If it seems you will not be able to gain access to the data you need, consider narrowing down your question to be more specific. 
• You have the expertise 
• You have the equipment and resources 
• Realistic: Developing your research question should be based on initial reading about your topic. It should focus on addressing a problem or gap in the existing knowledge in your field or discipline. 
• Based on some sort of rational physics 
• Can be done in a reasonable time frame 
• Timely: The research question should contribute to an existing and current debate in your field or in society at large. It should produce knowledge that future researchers or practitioners can later build on. 
• Novel 
• Based on current technologies. 
• Important to answer current problems or concerns. 
• Lead to new directions. 
• Important: Your question should have some aspect of originality. Incremental research is as important as exploring disruptive technologies. For example, you can focus on a specific location or explore a new angle. 
• Meaningful whether the answer is “Yes” or “No.” Closed-ended, yes/no questions are too simple to work as good research questions. Such questions do not provide enough scope for robust investigation and discussion. A good research question requires original data, synthesis of multiple sources, and original interpretation and argumentation before providing an answer. 

Steps for developing a good research question

The importance of research questions cannot be understated. When drafting a research question, use the following frameworks to guide the components of your question to ease the process. 4  

• Determine the requirements: Before constructing a good research question, set your research requirements. What is the purpose? Is it descriptive, comparative, or explorative research? Determining the research aim will help you choose the most appropriate topic and word your question appropriately. 
• Select a broad research topic: Identify a broader subject area of interest that requires investigation. Techniques such as brainstorming or concept mapping can help identify relevant connections and themes within a broad research topic. For example, how to learn and help students learn. 
• Perform preliminary investigation: Preliminary research is needed to obtain up-to-date and relevant knowledge on your topic. It also helps identify issues currently being discussed from which information gaps can be identified. 
• Narrow your focus: Narrow the scope and focus of your research to a specific niche. This involves focusing on gaps in existing knowledge or recent literature or extending or complementing the findings of existing literature. Another approach involves constructing strong research questions that challenge your views or knowledge of the area of study (Example: Is learning consistent with the existing learning theory and research). 
• Identify the research problem: Once the research question has been framed, one should evaluate it. This is to realize the importance of the research questions and if there is a need for more revising (Example: How do your beliefs on learning theory and research impact your instructional practices). 

How to write a research question

Those struggling to understand how to write a research question, these simple steps can help you simplify the process of writing a research question. 

Sample Research Questions

The following are some bad and good research question examples 

• Example 1 

• Example 2 

References:  

• Thabane, L., Thomas, T., Ye, C., & Paul, J. (2009). Posing the research question: not so simple.  Canadian Journal of Anesthesia/Journal canadien d’anesthésie ,  56 (1), 71-79. 
• Rutberg, S., & Bouikidis, C. D. (2018). Focusing on the fundamentals: A simplistic differentiation between qualitative and quantitative research.  Nephrology Nursing Journal ,  45 (2), 209-213. 
• Kyngäs, H. (2020). Qualitative research and content analysis.  The application of content analysis in nursing science research , 3-11. 
• Mattick, K., Johnston, J., & de la Croix, A. (2018). How to… write a good research question.  The clinical teacher ,  15 (2), 104-108. 
• Fandino, W. (2019). Formulating a good research question: Pearls and pitfalls.  Indian Journal of Anaesthesia ,  63 (8), 611. 
• Richardson, W. S., Wilson, M. C., Nishikawa, J., & Hayward, R. S. (1995). The well-built clinical question: a key to evidence-based decisions.  ACP journal club ,  123 (3), A12-A13 

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Formulating a Clear Research Question Statement

Formulating a clear research question is a crucial step in the research process, providing a focused, precise path for inquiry. This article outlines the essential steps and considerations for developing a strong research question that guides the entire research project.

Key Takeaways

• Understand the core attributes of a strong research question, including specificity, clarity, and relevance to the field of study.
• Identify common pitfalls in research question formulation, such as vagueness and overly broad scope, and learn strategies to avoid them.
• Utilize literature reviews effectively to refine and align your research question with existing knowledge and gaps.
• Transition smoothly from a well-formulated research question to a testable hypothesis, setting the foundation for your research methodology.
• Consider ethical implications in your research question to ensure fairness, privacy, and bias mitigation.

Understanding the Essence of a Research Question Statement

Defining a research question.

To embark on any research project, you must first clearly understand what a research question is. It is the fundamental query that guides your entire study, aiming to address a specific concern or gap in knowledge. Formulating a clear and concise research question is crucial as it sets the direction and scope of your investigation.

Characteristics of a Strong Research Question

A strong research question should be precise, manageable, and substantial enough to warrant detailed analysis. It should be researchable —meaning there must be enough evidence and resources available to answer it. Moreover, it should be specific enough to allow for a clear and focused investigation, yet broad enough to cover the necessary aspects of the topic.

Common Pitfalls to Avoid

When crafting your research question, avoid vagueness, overly broad topics, and questions that are too trivial. A common pitfall is formulating a question that is either too broad or too narrow, which can lead to either an overwhelming amount of data or a lack of sufficient information to conduct thorough research.

Developing a Research Question from a Broad Topic

Narrowing down the scope.

To transform a broad topic into a focused research question , start by identifying the specific aspects of the topic that intrigue you the most. This process involves breaking down the topic into manageable parts and deciding which part you are most passionate about or which has the least existing research.

Identifying Key Variables

Once you have a clearer scope, identify the key variables that will form the basis of your research. These variables are the elements within your topic that you can measure or assess to gather data. Understanding these variables is crucial for formulating an effective research question .

Formulating an Initial Question

With a specific aspect and key variables identified, you can now draft an initial question. This question should be clear, concise, and answerable within the constraints of your research resources. It's important to refine this question over time to ensure it remains relevant and focused on your research goals.

Evaluating the Clarity and Focus of Your Research Question

Criteria for clarity and specificity.

To ensure your research question is effective, it's crucial to evaluate its clarity and specificity. Ask yourself: Is my research question clear? It should be straightforward, with no ambiguity in its wording. Additionally, consider whether it is focused enough to guide your research without being overly broad or narrow.

Tools for Assessing Research Questions

Various tools and frameworks can help you assess the quality of your research question. Utilize checklists and guidelines that focus on the essential aspects of a good research question, such as its scope, relevance, and feasibility. These tools can provide a structured way to critique and refine your question.

Refining Your Question for Precision

After initial assessments, refine your research question to achieve greater precision. This involves narrowing down the scope and specifying the variables involved. Make adjustments based on feedback and ensure your question aligns closely with your research objectives. This step is vital for setting a solid foundation for your study.

The Role of Literature Review in Shaping Your Research Question

Exploring existing research.

When you begin your research journey, the first step is to immerse yourself in the existing body of knowledge. This involves thoroughly reviewing relevant literature to understand what has been studied, how it has been approached, and the outcomes of those studies. This foundational step not only broadens your understanding but also ensures that your research question is grounded in a solid context.

Identifying Gaps and Opportunities

As you delve deeper into the literature, your goal is to identify gaps or areas that have not been fully explored. This process of identifying gaps is crucial as it directs you to potential opportunities for original research. By pinpointing these areas, you can formulate a research question that contributes new insights to your field.

Aligning Your Question with Current Knowledge

Finally, ensure that your research question aligns with the current knowledge landscape. This alignment is essential for the relevance and feasibility of your study. It also helps in articulating how your research will build on, and differ from, existing studies. By aligning your question, you make a compelling case for the significance and necessity of your research.

Transforming a Research Question into a Hypothesis

From question to hypothesis.

Once you have a clear research question, the next step is to transform it into a hypothesis . A hypothesis is a predictive statement that bridges your research question with empirical testing. It's a crucial step in moving from theoretical exploration to concrete, testable predictions . Formulating a hypothesis requires a deep understanding of the variables involved and their possible interactions.

Testing Your Hypothesis

Testing your hypothesis is where your research takes a practical turn. Here, you design experiments or studies to see if the empirical evidence supports your hypothesis. This phase is critical as it directly addresses the validity of your predictions and by extension, the soundness of your research question.

Setting the Stage for Methodology

The final step in this transformation process is setting the stage for your methodology. This involves selecting the appropriate research methods and tools to effectively test your hypothesis. Whether it's qualitative or quantitative research, choosing the right methodology will significantly impact the accuracy and reliability of your results.

Ethical Considerations in Framing Research Questions

When you're formulating your research question, it's crucial to consider the ethical implications of your study. Ethical guidelines for research questions ensure that your inquiry respects the dignity and rights of participants. This involves obtaining informed consent, ensuring anonymity, and avoiding harm.

Avoiding Bias and Ensuring Fairness

Bias in research can skew results and lead to unethical outcomes. It's essential to design your study in a way that minimally influences the participants' responses or behaviors. This includes using neutral language and ensuring that your question does not lead or mislead participants.

Respecting Privacy and Confidentiality

Maintaining the privacy and confidentiality of your participants is a fundamental aspect of ethical research. This means carefully handling sensitive information and using data protection methods to secure personal data. It's important to outline how you will protect this information right from the start of your study.

Advanced Techniques for Crafting Precise Research Questions

Utilizing analytical frameworks.

To enhance the precision of your research questions, consider employing analytical frameworks. These tools help in dissecting the research problem into manageable components, allowing for a more targeted investigation. Frameworks such as SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis or PESTLE (Political, Economic, Social, Technological, Legal, Environmental) analysis can provide structured ways to explore various aspects of a topic.

Incorporating Theoretical Models

Theoretical models are instrumental in shaping well-defined research questions. By grounding your question within established theories, you ensure that your inquiry is not only relevant but also anchored in a solid academic foundation. Utilizing models from your field can guide the formulation of questions that are both innovative and deeply rooted in scholarly traditions.

Leveraging Statistical Tools for Precision

Statistical tools are essential for refining research questions to ensure they are specific and measurable. Techniques such as regression analysis or factor analysis can help you identify and define the key variables in your study. This approach not only enhances the clarity of your research question but also boosts its methodological rigor, making your findings more robust and credible.

Dive deeper into the realm of academic success with our article on 'Advanced Techniques for Crafting Precise Research Questions'. This guide is meticulously designed to enhance your research skills and refine your academic inquiries. Don't miss out on elevating your thesis to the next level. Visit our website to explore more insightful content and claim your special offer today!

In conclusion, formulating a clear research question is a pivotal step in the research process that sets the stage for a focused and meaningful study. A well-crafted question not only guides the research direction but also sharpens the study's objectives, ensuring that the investigation remains on track and relevant. It is essential for researchers to invest time in refining their research question, making sure it is specific, researchable, and significant within their field. By adhering to these principles, researchers can enhance the clarity and impact of their studies, contributing valuable insights to their academic disciplines.

Frequently Asked Questions

What is a research question statement.

A research question statement clearly defines the focus of a study. It outlines the central issue or problem that the research aims to address, guiding the direction and scope of the investigation.

What makes a strong research question?

A strong research question is specific, clear, feasible, relevant, and complex enough to allow for detailed exploration and analysis within the scope of the study.

How can I narrow down a broad topic into a research question?

To narrow down a broad topic, identify key themes or issues within the topic, review related literature to find gaps, and use these insights to formulate a focused question that addresses a specific aspect of the topic.

What role does literature review play in formulating a research question?

A literature review helps to identify gaps in existing research, which can inspire new research questions. It also ensures that the question aligns with current knowledge and advances the understanding of the topic.

How do I transform a research question into a hypothesis?

To transform a research question into a hypothesis, restate the question as a statement that predicts an outcome based on theoretical insights or previous research. This hypothesis can then be tested through your study's methodology.

What are some ethical considerations in framing research questions?

Ethical considerations include ensuring the question does not harm participants, respects privacy and confidentiality, avoids bias, and contributes positively to the field of study.

How to Ask a Research Question: Crafting Inquiries that Matter

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How to write a research plan: Step-by-step guide

Last updated

30 January 2024

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Today’s businesses and institutions rely on data and analytics to inform their product and service decisions. These metrics influence how organizations stay competitive and inspire innovation. However, gathering data and insights requires carefully constructed research, and every research project needs a roadmap. This is where a research plan comes into play.

Read this step-by-step guide for writing a detailed research plan that can apply to any project, whether it’s scientific, educational, or business-related.

• What is a research plan?

A research plan is a documented overview of a project in its entirety, from end to end. It details the research efforts, participants, and methods needed, along with any anticipated results. It also outlines the project’s goals and mission, creating layers of steps to achieve those goals within a specified timeline.

Without a research plan, you and your team are flying blind, potentially wasting time and resources to pursue research without structured guidance.

The principal investigator, or PI, is responsible for facilitating the research oversight. They will create the research plan and inform team members and stakeholders of every detail relating to the project. The PI will also use the research plan to inform decision-making throughout the project.

• Why do you need a research plan?

Create a research plan before starting any official research to maximize every effort in pursuing and collecting the research data. Crucially, the plan will model the activities needed at each phase of the research project .

Like any roadmap, a research plan serves as a valuable tool providing direction for those involved in the project—both internally and externally. It will keep you and your immediate team organized and task-focused while also providing necessary definitions and timelines so you can execute your project initiatives with full understanding and transparency.

External stakeholders appreciate a working research plan because it’s a great communication tool, documenting progress and changing dynamics as they arise. Any participants of your planned research sessions will be informed about the purpose of your study, while the exercises will be based on the key messaging outlined in the official plan.

Here are some of the benefits of creating a research plan document for every project:

Project organization and structure

Well-informed participants

All stakeholders and teams align in support of the project

Clearly defined project definitions and purposes

Distractions are eliminated, prioritizing task focus

Timely management of individual task schedules and roles

Costly reworks are avoided

• What should a research plan include?

The different aspects of your research plan will depend on the nature of the project. However, most official research plan documents will include the core elements below. Each aims to define the problem statement , devising an official plan for seeking a solution.

Specific project goals and individual objectives

Ideal strategies or methods for reaching those goals

Required resources

Descriptions of the target audience, sample sizes , demographics, and scopes

Key performance indicators (KPIs)

Project background

Research and testing support

Preliminary studies and progress reporting mechanisms

Cost estimates and change order processes

Depending on the research project’s size and scope, your research plan could be brief—perhaps only a few pages of documented plans. Alternatively, it could be a fully comprehensive report. Either way, it’s an essential first step in dictating your project’s facilitation in the most efficient and effective way.

• How to write a research plan for your project

When you start writing your research plan, aim to be detailed about each step, requirement, and idea. The more time you spend curating your research plan, the more precise your research execution efforts will be.

Account for every potential scenario, and be sure to address each and every aspect of the research.

Consider following this flow to develop a great research plan for your project:

Define your project’s purpose

Start by defining your project’s purpose. Identify what your project aims to accomplish and what you are researching. Remember to use clear language.

Thinking about the project’s purpose will help you set realistic goals and inform how you divide tasks and assign responsibilities. These individual tasks will be your stepping stones to reach your overarching goal.

Additionally, you’ll want to identify the specific problem, the usability metrics needed, and the intended solutions.

Know the following three things about your project’s purpose before you outline anything else:

What you’re doing

Why you’re doing it

What you expect from it

Identify individual objectives

With your overarching project objectives in place, you can identify any individual goals or steps needed to reach those objectives. Break them down into phases or steps. You can work backward from the project goal and identify every process required to facilitate it.

Be mindful to identify each unique task so that you can assign responsibilities to various team members. At this point in your research plan development, you’ll also want to assign priority to those smaller, more manageable steps and phases that require more immediate or dedicated attention.

Select research methods

Once you have outlined your goals, objectives, steps, and tasks, it’s time to drill down on selecting research methods . You’ll want to leverage specific research strategies and processes. When you know what methods will help you reach your goals, you and your teams will have direction to perform and execute your assigned tasks.

Research methods might include any of the following:

User interviews : this is a qualitative research method where researchers engage with participants in one-on-one or group conversations. The aim is to gather insights into their experiences, preferences, and opinions to uncover patterns, trends, and data.

Field studies : this approach allows for a contextual understanding of behaviors, interactions, and processes in real-world settings. It involves the researcher immersing themselves in the field, conducting observations, interviews, or experiments to gather in-depth insights.

Card sorting : participants categorize information by sorting content cards into groups based on their perceived similarities. You might use this process to gain insights into participants’ mental models and preferences when navigating or organizing information on websites, apps, or other systems.

Focus groups : use organized discussions among select groups of participants to provide relevant views and experiences about a particular topic.

Diary studies : ask participants to record their experiences, thoughts, and activities in a diary over a specified period. This method provides a deeper understanding of user experiences, uncovers patterns, and identifies areas for improvement.

Five-second testing: participants are shown a design, such as a web page or interface, for just five seconds. They then answer questions about their initial impressions and recall, allowing you to evaluate the design’s effectiveness.

Surveys : get feedback from participant groups with structured surveys. You can use online forms, telephone interviews, or paper questionnaires to reveal trends, patterns, and correlations.

Tree testing : tree testing involves researching web assets through the lens of findability and navigability. Participants are given a textual representation of the site’s hierarchy (the “tree”) and asked to locate specific information or complete tasks by selecting paths.

Usability testing : ask participants to interact with a product, website, or application to evaluate its ease of use. This method enables you to uncover areas for improvement in digital key feature functionality by observing participants using the product.

Live website testing: research and collect analytics that outlines the design, usability, and performance efficiencies of a website in real time.

There are no limits to the number of research methods you could use within your project. Just make sure your research methods help you determine the following:

What do you plan to do with the research findings?

What decisions will this research inform? How can your stakeholders leverage the research data and results?

Recruit participants and allocate tasks

Next, identify the participants needed to complete the research and the resources required to complete the tasks. Different people will be proficient at different tasks, and having a task allocation plan will allow everything to run smoothly.

Prepare a thorough project summary

Every well-designed research plan will feature a project summary. This official summary will guide your research alongside its communications or messaging. You’ll use the summary while recruiting participants and during stakeholder meetings. It can also be useful when conducting field studies.

Ensure this summary includes all the elements of your research project . Separate the steps into an easily explainable piece of text that includes the following:

An introduction: the message you’ll deliver to participants about the interview, pre-planned questioning, and testing tasks.

Interview questions: prepare questions you intend to ask participants as part of your research study, guiding the sessions from start to finish.

An exit message: draft messaging your teams will use to conclude testing or survey sessions. These should include the next steps and express gratitude for the participant’s time.

Create a realistic timeline

While your project might already have a deadline or a results timeline in place, you’ll need to consider the time needed to execute it effectively.

Realistically outline the time needed to properly execute each supporting phase of research and implementation. And, as you evaluate the necessary schedules, be sure to include additional time for achieving each milestone in case any changes or unexpected delays arise.

For this part of your research plan, you might find it helpful to create visuals to ensure your research team and stakeholders fully understand the information.

Determine how to present your results

A research plan must also describe how you intend to present your results. Depending on the nature of your project and its goals, you might dedicate one team member (the PI) or assume responsibility for communicating the findings yourself.

In this part of the research plan, you’ll articulate how you’ll share the results. Detail any materials you’ll use, such as:

Presentations and slides

A project report booklet

A project findings pamphlet

Documents with key takeaways and statistics

Graphic visuals to support your findings

• Format your research plan

As you create your research plan, you can enjoy a little creative freedom. A plan can assume many forms, so format it how you see fit. Determine the best layout based on your specific project, intended communications, and the preferences of your teams and stakeholders.

Find format inspiration among the following layouts:

Written outlines

Narrative storytelling

Visual mapping

Graphic timelines

Remember, the research plan format you choose will be subject to change and adaptation as your research and findings unfold. However, your final format should ideally outline questions, problems, opportunities, and expectations.

• Research plan example

Imagine you’ve been tasked with finding out how to get more customers to order takeout from an online food delivery platform. The goal is to improve satisfaction and retain existing customers. You set out to discover why more people aren’t ordering and what it is they do want to order or experience. 

You identify the need for a research project that helps you understand what drives customer loyalty . But before you jump in and start calling past customers, you need to develop a research plan—the roadmap that provides focus, clarity, and realistic details to the project.

Here’s an example outline of a research plan you might put together:

Project title

Project members involved in the research plan

Purpose of the project (provide a summary of the research plan’s intent)

Objective 1 (provide a short description for each objective)

Objective 2

Objective 3

Proposed timeline

Audience (detail the group you want to research, such as customers or non-customers)

Budget (how much you think it might cost to do the research)

Risk factors/contingencies (any potential risk factors that may impact the project’s success)

Remember, your research plan doesn’t have to reinvent the wheel—it just needs to fit your project’s unique needs and aims.

Customizing a research plan template

Some companies offer research plan templates to help get you started. However, it may make more sense to develop your own customized plan template. Be sure to include the core elements of a great research plan with your template layout, including the following:

Introductions to participants and stakeholders

Background problems and needs statement

Significance, ethics, and purpose

Research methods, questions, and designs

Preliminary beliefs and expectations

Implications and intended outcomes

Realistic timelines for each phase

Conclusion and presentations

How many pages should a research plan be?

Generally, a research plan can vary in length between 500 to 1,500 words. This is roughly three pages of content. More substantial projects will be 2,000 to 3,500 words, taking up four to seven pages of planning documents.

What is the difference between a research plan and a research proposal?

A research plan is a roadmap to success for research teams. A research proposal, on the other hand, is a dissertation aimed at convincing or earning the support of others. Both are relevant in creating a guide to follow to complete a project goal.

What are the seven steps to developing a research plan?

While each research project is different, it’s best to follow these seven general steps to create your research plan:

Defining the problem

Identifying goals

Choosing research methods

Recruiting participants

Preparing the brief or summary

Establishing task timelines

Defining how you will present the findings

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Writing Studio

Formulating your research question (rq).

In an effort to make our handouts more accessible, we have begun converting our PDF handouts to web pages. Download this page as a PDF: Formulating Your Research Question Return to Writing Studio Handouts

In a research paper, the emphasis is on generating a unique question and then synthesizing diverse sources into a coherent essay that supports your argument about the topic. In other words, you integrate information from publications with your own thoughts in order to formulate an argument. Your topic is your starting place: from here, you will develop an engaging research question. Merely presenting a topic in the form of a question does not transform it into a good research question.

Research Topic Versus Research Question Examples

1. broad topic versus narrow question, 1a. broad topic.

“What forces affect race relations in America?”

1b. NARROWER QUESTION

“How do corporate hiring practices affect race relations in Nashville?”

The question “What is the percentage of racial minorities holding management positions in corporate offices in Nashville?” is much too specific and would yield, at best, a statistic that could become part of a larger argument.

2. Neutral Topic Versus Argumentative Question

2a. neutral topic.

“How does KFC market its low-fat food offerings?”

2b. Argumentative question

“Does KFC put more money into marketing its high-fat food offerings than its lower-fat ones?”

The latter question is somewhat better, since it may lead you to take a stance or formulate an argument about consumer awareness or benefit.

3. Objective Topic Versus Subjective Question

Objective subjects are factual and do not have sides to be argued. Subjective subjects are those about which you can take a side.

3a. Objective topic

“How much time do youth between the ages of 10 and 15 spend playing video games?”

3b. Subjective Question

“What are the effects of video-gaming on the attention spans of youth between the ages of 10 and 15?”

The first question is likely to lead to some data, though not necessarily to an argument or issue. The second question is somewhat better, since it might lead you to formulate an argument for or against time spent playing video games.

4. Open-Ended Topic Versus Direct Question

4a. open-ended topic.

“Does the author of this text use allusion?”

4b. Direct question (gives direction to research)

“Does the ironic use of allusion in this text reveal anything about the author’s unwillingness to divulge his political commitments?”

The second question gives focus by putting the use of allusion into the specific context of a question about the author’s political commitments and perhaps also about the circumstances under which the text was produced.

Research Question (RQ) Checklist

• Is my RQ something that I am curious about and that others might care about? Does it present an issue on which I can take a stand?
• Does my RQ put a new spin on an old issue, or does it try to solve a problem?
• Is my RQ too broad, too narrow, or OK?
• within the time frame of the assignment?
• given the resources available at my location?
• Is my RQ measurable? What type of information do I need? Can I find actual data to support or contradict a position?
• What sources will have the type of information that I need to answer my RQ (journals, books, internet resources, government documents, interviews with people)?

Final Thoughts

The answer to a good research question will often be the THESIS of your research paper! And the results of your research may not always be what you expected them to be. Not only is this ok, it can be an indication that you are doing careful work!

Adapted from an online tutorial at Empire State College: http://www.esc.edu/htmlpages/writerold/menus.htm#develop (broken link)

Last revised: November 2022 | Adapted for web delivery: November 2022

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Illustration by James Round

How to plan a research project

Whether for a paper or a thesis, define your question, review the work of others – and leave yourself open to discovery.

by Brooke Harrington   + BIO

is professor of sociology at Dartmouth College in New Hampshire. Her research has won international awards both for scholarly quality and impact on public life. She has published dozens of articles and three books, most recently the bestseller Capital without Borders (2016), now translated into five languages.

Edited by Sam Haselby

Need to know

‘When curiosity turns to serious matters, it’s called research.’ – From Aphorisms (1880-1905) by Marie von Ebner-Eschenbach

Planning research projects is a time-honoured intellectual exercise: one that requires both creativity and sharp analytical skills. The purpose of this Guide is to make the process systematic and easy to understand. While there is a great deal of freedom and discovery involved – from the topics you choose, to the data and methods you apply – there are also some norms and constraints that obtain, no matter what your academic level or field of study. For those in high school through to doctoral students, and from art history to archaeology, research planning involves broadly similar steps, including: formulating a question, developing an argument or predictions based on previous research, then selecting the information needed to answer your question.

Some of this might sound self-evident but, as you’ll find, research requires a different way of approaching and using information than most of us are accustomed to in everyday life. That is why I include orienting yourself to knowledge-creation as an initial step in the process. This is a crucial and underappreciated phase in education, akin to making the transition from salaried employment to entrepreneurship: suddenly, you’re on your own, and that requires a new way of thinking about your work.

What follows is a distillation of what I’ve learned about this process over 27 years as a professional social scientist. It reflects the skills that my own professors imparted in the sociology doctoral programme at Harvard, as well as what I learned later on as a research supervisor for Ivy League PhD and MA students, and then as the author of award-winning scholarly books and articles. It can be adapted to the demands of both short projects (such as course term papers) and long ones, such as a thesis.

At its simplest, research planning involves the four distinct steps outlined below: orienting yourself to knowledge-creation; defining your research question; reviewing previous research on your question; and then choosing relevant data to formulate your own answers. Because the focus of this Guide is on planning a research project, as opposed to conducting a research project, this section won’t delve into the details of data-collection or analysis; those steps happen after you plan the project. In addition, the topic is vast: year-long doctoral courses are devoted to data and analysis. Instead, the fourth part of this section will outline some basic strategies you could use in planning a data-selection and analysis process appropriate to your research question.

Step 1: Orient yourself

Planning and conducting research requires you to make a transition, from thinking like a consumer of information to thinking like a producer of information. That sounds simple, but it’s actually a complex task. As a practical matter, this means putting aside the mindset of a student, which treats knowledge as something created by other people. As students, we are often passive receivers of knowledge: asked to do a specified set of readings, then graded on how well we reproduce what we’ve read.

Researchers, however, must take on an active role as knowledge producers . Doing research requires more of you than reading and absorbing what other people have written: you have to engage in a dialogue with it. That includes arguing with previous knowledge and perhaps trying to show that ideas we have accepted as given are actually wrong or incomplete. For example, rather than simply taking in the claims of an author you read, you’ll need to draw out the implications of those claims: if what the author is saying is true, what else does that suggest must be true? What predictions could you make based on the author’s claims?

In other words, rather than treating a reading as a source of truth – even if it comes from a revered source, such as Plato or Marie Curie – this orientation step asks you to treat the claims you read as provisional and subject to interrogation. That is one of the great pieces of wisdom that science and philosophy can teach us: that the biggest advances in human understanding have been made not by being correct about trivial things, but by being wrong in an interesting way . For example, Albert Einstein was wrong about quantum mechanics, but his arguments about it with his fellow physicist Niels Bohr have led to some of the biggest breakthroughs in science, even a century later.

Step 2: Define your research question

Students often give this step cursory attention, but experienced researchers know that formulating a good question is sometimes the most difficult part of the research planning process. That is because the precise language of the question frames the rest of the project. It’s therefore important to pose the question carefully, in a way that’s both possible to answer and likely to yield interesting results. Of course, you must choose a question that interests you, but that’s only the beginning of what’s likely to be an iterative process: most researchers come back to this step repeatedly, modifying their questions in light of previous research, resource limitations and other considerations.

Researchers face limits in terms of time and money. They, like everyone else, have to pose research questions that they can plausibly answer given the constraints they face. For example, it would be inadvisable to frame a project around the question ‘What are the roots of the Arab-Israeli conflict?’ if you have only a week to develop an answer and no background on that topic. That’s not to limit your imagination: you can come up with any question you’d like. But it typically does require some creativity to frame a question that you can answer well – that is, by investigating thoroughly and providing new insights – within the limits you face.

In addition to being interesting to you, and feasible within your resource constraints, the third and most important characteristic of a ‘good’ research topic is whether it allows you to create new knowledge. It might turn out that your question has already been asked and answered to your satisfaction: if so, you’ll find out in the next step of this process. On the other hand, you might come up with a research question that hasn’t been addressed previously. Before you get too excited about breaking uncharted ground, consider this: a lot of potentially researchable questions haven’t been studied for good reason ; they might have answers that are trivial or of very limited interest. This could include questions such as ‘Why does the area of a circle equal π r²?’ or ‘Did winter conditions affect Napoleon’s plans to invade Russia?’ Of course, you might be able to make the argument that a seemingly trivial question is actually vitally important, but you must be prepared to back that up with convincing evidence. The exercise in the ‘Learn More’ section below will help you think through some of these issues.

Finally, scholarly research questions must in some way lead to new and distinctive insights. For example, lots of people have studied gender roles in sports teams; what can you ask that hasn’t been asked before? Reinventing the wheel is the number-one no-no in this endeavour. That’s why the next step is so important: reviewing previous research on your topic. Depending on what you find in that step, you might need to revise your research question; iterating between your question and the existing literature is a normal process. But don’t worry: it doesn’t go on forever. In fact, the iterations taper off – and your research question stabilises – as you develop a firm grasp of the current state of knowledge on your topic.

Step 3: Review previous research

In academic research, from articles to books, it’s common to find a section called a ‘literature review’. The purpose of that section is to describe the state of the art in knowledge on the research question that a project has posed. It demonstrates that researchers have thoroughly and systematically reviewed the relevant findings of previous studies on their topic, and that they have something novel to contribute.

Your own research project should include something like this, even if it’s a high-school term paper. In the research planning process, you’ll want to list at least half a dozen bullet points stating the major findings on your topic by other people. In relation to those findings, you should be able to specify where your project could provide new and necessary insights. There are two basic rhetorical positions one can take in framing the novelty-plus-importance argument required of academic research:

• Position 1 requires you to build on or extend a set of existing ideas; that means saying something like: ‘Person A has argued that X is true about gender; this implies Y, which has not yet been tested. My project will test Y, and if I find evidence to support it, that will change the way we understand gender.’
• Position 2 is to argue that there is a gap in existing knowledge, either because previous research has reached conflicting conclusions or has failed to consider something important. For example, one could say that research on middle schoolers and gender has been limited by being conducted primarily in coeducational environments, and that findings might differ dramatically if research were conducted in more schools where the student body was all-male or all-female.

Your overall goal in this step of the process is to show that your research will be part of a larger conversation: that is, how your project flows from what’s already known, and how it advances, extends or challenges that existing body of knowledge. That will be the contribution of your project, and it constitutes the motivation for your research.

Two things are worth mentioning about your search for sources of relevant previous research. First, you needn’t look only at studies on your precise topic. For example, if you want to study gender-identity formation in schools, you shouldn’t restrict yourself to studies of schools; the empirical setting (schools) is secondary to the larger social process that interests you (how people form gender identity). That process occurs in many different settings, so cast a wide net. Second, be sure to use legitimate sources – meaning publications that have been through some sort of vetting process, whether that involves peer review (as with academic journal articles you might find via Google Scholar) or editorial review (as you’d find in well-known mass media publications, such as The Economist or The Washington Post ). What you’ll want to avoid is using unvetted sources such as personal blogs or Wikipedia. Why? Because anybody can write anything in those forums, and there is no way to know – unless you’re already an expert – if the claims you find there are accurate. Often, they’re not.

Step 4: Choose your data and methods

Whatever your research question is, eventually you’ll need to consider which data source and analytical strategy are most likely to provide the answers you’re seeking. One starting point is to consider whether your question would be best addressed by qualitative data (such as interviews, observations or historical records), quantitative data (such as surveys or census records) or some combination of both. Your ideas about data sources will, in turn, suggest options for analytical methods.

You might need to collect your own data, or you might find everything you need readily available in an existing dataset someone else has created. A great place to start is with a research librarian: university libraries always have them and, at public universities, those librarians can work with the public, including people who aren’t affiliated with the university. If you don’t happen to have a public university and its library close at hand, an ordinary public library can still be a good place to start: the librarians are often well versed in accessing data sources that might be relevant to your study, such as the census, or historical archives, or the Survey of Consumer Finances.

Because your task at this point is to plan research, rather than conduct it, the purpose of this step is not to commit you irrevocably to a course of action. Instead, your goal here is to think through a feasible approach to answering your research question. You’ll need to find out, for example, whether the data you want exist; if not, do you have a realistic chance of gathering the data yourself, or would it be better to modify your research question? In terms of analysis, would your strategy require you to apply statistical methods? If so, do you have those skills? If not, do you have time to learn them, or money to hire a research assistant to run the analysis for you?

Please be aware that qualitative methods in particular are not the casual undertaking they might appear to be. Many people make the mistake of thinking that only quantitative data and methods are scientific and systematic, while qualitative methods are just a fancy way of saying: ‘I talked to some people, read some old newspapers, and drew my own conclusions.’ Nothing could be further from the truth. In the final section of this guide, you’ll find some links to resources that will provide more insight on standards and procedures governing qualitative research, but suffice it to say: there are rules about what constitutes legitimate evidence and valid analytical procedure for qualitative data, just as there are for quantitative data.

Circle back and consider revising your initial plans

As you work through these four steps in planning your project, it’s perfectly normal to circle back and revise. Research planning is rarely a linear process. It’s also common for new and unexpected avenues to suggest themselves. As the sociologist Thorstein Veblen wrote in 1908 : ‘The outcome of any serious research can only be to make two questions grow where only one grew before.’ That’s as true of research planning as it is of a completed project. Try to enjoy the horizons that open up for you in this process, rather than becoming overwhelmed; the four steps, along with the two exercises that follow, will help you focus your plan and make it manageable.

Key points – How to plan a research project

• Planning a research project is essential no matter your academic level or field of study. There is no one ‘best’ way to design research, but there are certain guidelines that can be helpfully applied across disciplines.
• Orient yourself to knowledge-creation. Make the shift from being a consumer of information to being a producer of information.
• Define your research question. Your question frames the rest of your project, sets the scope, and determines the kinds of answers you can find.
• Review previous research on your question. Survey the existing body of relevant knowledge to ensure that your research will be part of a larger conversation.
• Choose your data and methods. For instance, will you be collecting qualitative data, via interviews, or numerical data, via surveys?
• Circle back and consider revising your initial plans. Expect your research question in particular to undergo multiple rounds of refinement as you learn more about your topic.

Good research questions tend to beget more questions. This can be frustrating for those who want to get down to business right away. Try to make room for the unexpected: this is usually how knowledge advances. Many of the most significant discoveries in human history have been made by people who were looking for something else entirely. There are ways to structure your research planning process without over-constraining yourself; the two exercises below are a start, and you can find further methods in the Links and Books section.

The following exercise provides a structured process for advancing your research project planning. After completing it, you’ll be able to do the following:

• describe clearly and concisely the question you’ve chosen to study
• summarise the state of the art in knowledge about the question, and where your project could contribute new insight
• identify the best strategy for gathering and analysing relevant data

In other words, the following provides a systematic means to establish the building blocks of your research project.

Exercise 1: Definition of research question and sources

This exercise prompts you to select and clarify your general interest area, develop a research question, and investigate sources of information. The annotated bibliography will also help you refine your research question so that you can begin the second assignment, a description of the phenomenon you wish to study.

Jot down a few bullet points in response to these two questions, with the understanding that you’ll probably go back and modify your answers as you begin reading other studies relevant to your topic:

• What will be the general topic of your paper?
• What will be the specific topic of your paper?

b) Research question(s)

Use the following guidelines to frame a research question – or questions – that will drive your analysis. As with Part 1 above, you’ll probably find it necessary to change or refine your research question(s) as you complete future assignments.

• Your question should be phrased so that it can’t be answered with a simple ‘yes’ or ‘no’.
• Your question should have more than one plausible answer.
• Your question should draw relationships between two or more concepts; framing the question in terms of How? or What? often works better than asking Why ?

c) Annotated bibliography

Most or all of your background information should come from two sources: scholarly books and journals, or reputable mass media sources. You might be able to access journal articles electronically through your library, using search engines such as JSTOR and Google Scholar. This can save you a great deal of time compared with going to the library in person to search periodicals. General news sources, such as those accessible through LexisNexis, are acceptable, but should be cited sparingly, since they don’t carry the same level of credibility as scholarly sources. As discussed above, unvetted sources such as blogs and Wikipedia should be avoided, because the quality of the information they provide is unreliable and often misleading.

To create an annotated bibliography, provide the following information for at least 10 sources relevant to your specific topic, using the format suggested below.

Name of author(s):

Publication date:

Title of book, chapter, or article:

If a chapter or article, title of journal or book where they appear:

Brief description of this work, including main findings and methods ( c 75 words):

Summary of how this work contributes to your project ( c 75 words):

Brief description of the implications of this work ( c 25 words):

Identify any gap or controversy in knowledge this work points up, and how your project could address those problems ( c 50 words):

Exercise 2: Towards an analysis

Develop a short statement ( c 250 words) about the kind of data that would be useful to address your research question, and how you’d analyse it. Some questions to consider in writing this statement include:

• What are the central concepts or variables in your project? Offer a brief definition of each.
• Do any data sources exist on those concepts or variables, or would you need to collect data?
• Of the analytical strategies you could apply to that data, which would be the most appropriate to answer your question? Which would be the most feasible for you? Consider at least two methods, noting their advantages or disadvantages for your project.

Links & books

One of the best texts ever written about planning and executing research comes from a source that might be unexpected: a 60-year-old work on urban planning by a self-trained scholar. The classic book The Death and Life of Great American Cities (1961) by Jane Jacobs (available complete and free of charge via this link ) is worth reading in its entirety just for the pleasure of it. But the final 20 pages – a concluding chapter titled ‘The Kind of Problem a City Is’ – are really about the process of thinking through and investigating a problem. Highly recommended as a window into the craft of research.

Jacobs’s text references an essay on advancing human knowledge by the mathematician Warren Weaver. At the time, Weaver was director of the Rockefeller Foundation, in charge of funding basic research in the natural and medical sciences. Although the essay is titled ‘A Quarter Century in the Natural Sciences’ (1960) and appears at first blush to be merely a summation of one man’s career, it turns out to be something much bigger and more interesting: a meditation on the history of human beings seeking answers to big questions about the world. Weaver goes back to the 17th century to trace the origins of systematic research thinking, with enthusiasm and vivid anecdotes that make the process come alive. The essay is worth reading in its entirety, and is available free of charge via this link .

For those seeking a more in-depth, professional-level discussion of the logic of research design, the political scientist Harvey Starr provides insight in a compact format in the article ‘Cumulation from Proper Specification: Theory, Logic, Research Design, and “Nice” Laws’ (2005). Starr reviews the ‘research triad’, consisting of the interlinked considerations of formulating a question, selecting relevant theories and applying appropriate methods. The full text of the article, published in the scholarly journal Conflict Management and Peace Science , is available, free of charge, via this link .

Finally, the book Getting What You Came For (1992) by Robert Peters is not only an outstanding guide for anyone contemplating graduate school – from the application process onward – but it also includes several excellent chapters on planning and executing research, applicable across a wide variety of subject areas. It was an invaluable resource for me 25 years ago, and it remains in print with good reason; I recommend it to all my students, particularly Chapter 16 (‘The Thesis Topic: Finding It’), Chapter 17 (‘The Thesis Proposal’) and Chapter 18 (‘The Thesis: Writing It’).

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FLEET LIBRARY | Research Guides

Rhode island school of design, create a research plan: research plan.

• Research Plan
• Literature Review
• Ulrich's Global Serials Directory
• Related Guides

A research plan is a framework that shows how you intend to approach your topic. The plan can take many forms: a written outline, a narrative, a visual/concept map or timeline. It's a document that will change and develop as you conduct your research. Components of a research plan

1. Research conceptualization - introduces your research question

2. Research methodology - describes your approach to the research question

3. Literature review, critical evaluation and synthesis - systematic approach to locating,

    reviewing and evaluating the work (text, exhibitions, critiques, etc) relating to your topic

4. Communication - geared toward an intended audience, shows evidence of your inquiry

Research conceptualization refers to the ability to identify specific research questions, problems or opportunities that are worthy of inquiry. Research conceptualization also includes the skills and discipline that go beyond the initial moment of conception, and which enable the researcher to formulate and develop an idea into something researchable ( Newbury 373).

Research methodology refers to the knowledge and skills required to select and apply appropriate methods to carry through the research project ( Newbury 374) .

Method describes a single mode of proceeding; methodology describes the overall process.

Method - a way of doing anything especially according to a defined and regular plan; a mode of procedure in any activity

Methodology - the study of the direction and implications of empirical research, or the sustainability of techniques employed in it; a method or body of methods used in a particular field of study or activity *Browse a list of research methodology books  or this guide on Art & Design Research

Literature Review, critical evaluation & synthesis

A literature review is a systematic approach to locating, reviewing, and evaluating the published work and work in progress of scholars, researchers, and practitioners on a given topic.

Critical evaluation and synthesis is the ability to handle (or process) existing sources. It includes knowledge of the sources of literature and contextual research field within which the person is working ( Newbury 373).

Literature reviews are done for many reasons and situations. Here's a short list:

Sources to consult while conducting a literature review:

Online catalogs of local, regional, national, and special libraries

meta-catalogs such as worldcat , Art Discovery Group , europeana , world digital library or RIBA

subject-specific online article databases (such as the Avery Index, JSTOR, Project Muse)

digital institutional repositories such as Digital Commons @RISD ; see Registry of Open Access Repositories

Open Access Resources recommended by RISD Research LIbrarians

works cited in scholarly books and articles

print bibliographies

the internet-locate major nonprofit, research institutes, museum, university, and government websites

search google scholar to locate grey literature & referenced citations

trade and scholarly publishers

fellow scholars and peers

Communication                              

Communication refers to the ability to

• structure a coherent line of inquiry
• communicate your findings to your intended audience
• make skilled use of visual material to express ideas for presentations, writing, and the creation of exhibitions ( Newbury 374)

Research plan framework: Newbury, Darren. "Research Training in the Creative Arts and Design." The Routledge Companion to Research in the Arts . Ed. Michael Biggs and Henrik Karlsson. New York: Routledge, 2010. 368-87. Print.

About the author

Except where otherwise noted, this guide is subject to a Creative Commons Attribution license

source document

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Formulating a researchable question: A critical step for facilitating good clinical research

Sadaf aslam.

Clinical and Translational Science Institute and Department of Internal Medicine, College of Medicine, University of South Florida, Tampa, FL, USA

Patricia Emmanuel

Developing a researchable question is one of the challenging tasks a researcher encounters when initiating a project. Both, unanswered issues in current clinical practice or when experiences dictate alternative therapies may provoke an investigator to formulate a clinical research question. This article will assist researchers by providing step-by-step guidance on the formulation of a research question. This paper also describes PICO (population, intervention, control, and outcomes) criteria in framing a research question. Finally, we also assess the characteristics of a research question in the context of initiating a research project.

INTRODUCTION

A researchable question is an uncertainty about a problem that can be challenged, examined, and analyzed to provide useful information.[ 1 ] A successful research project depends upon how well an investigator formulates the research question based on the problems faced in day-to-day research activities and clinical practice. The underlying questions of a research project provide important information to decide whether the topic is relevant, researchable, and significant. A well-formulated research question needs extreme specificity and preciseness which guides the implementation of the project keeping in mind the identification of variables and population of interest. Here we will present a clinical scenario and see how clinical questions arise and help us in finding the evidence to answer our question.

FORMULATING THE RESEARCH QUESTION

A 2-year-old boy presents in an outpatient clinic with fever and severe pain in his right ear. He has a history of recurrent ear infections, and his mother expresses a concern that he has been on the antibiotic amoxicillin for the past few weeks. She is worried about the consequences of the long-term antibiotic use. She is also concerned about the outcome associated with recurrent ear infections. She wants to know if the prescribed amoxicillin is effective, or it can be substituted with another antibiotic because of its side effects such as frequent diarrhea.

Several questions arise from this case which can be broadly classified into background and foreground questions. The general questions about a clinical problem or a disease are called “Background Questions.”[ 2 ] These questions generally ask what, when, how, and where about the disease, disorder, or treatment for instance, “What is otitis media?” or “How does amoxicillin work?” etc. These types of questions can be answered by going through review articles or text books.

The patient-oriented questions involving interpretation of a therapy or disease and consideration of risk vs. benefit for a patient or a group of patient are called “Foreground Questions.”[ 2 ] These types of complex clinical questions are best answered by primary or pre-assessed studies in the literature. These questions mostly compare the two, either two drugs or treatments or two diagnostic methods, etc.

The PICO (population, intervention, control, and outcomes) format [ Table 1 ] is considered a widely known strategy for framing a “foreground” research question.[ 3 ] Sackett et al . pointed out that breaking the question into four components will facilitate the identification of relevant information.

Considering PICO and FINER criteria for developing a research question[ 3 , 5 ]

Population or problem - addressing a specific population, its important characteristics and demographic information. From the above case, you can identify pediatric population with otitis media, the age range, sex, presenting complaint, and history.

Intervention or treatment of interest - the intervention can be a treatment, procedure, diagnostic test, and risk or prognostic factors. In this case, the intervention will be your plan to treat the patient which can be a new therapy, a diagnostic test, prognostic factor, or a procedure. For example, based on your observation in clinic, cefuroxime is another better treatment option as compared to amoxicillin in treating otitis media but you are not sure about its efficacy in pediatric population with otitis media.

Comparator or control -when a new therapy is compared with the existing one.

Outcome - is the effect of the intervention. For example, its effectiveness in controlling pain. Therefore, the outcome in the above case can be the relief of pain, the resolution of infection, or decreasing the risk of developing resistance. A good primary outcome should be easily quantifiable, specific, valid, reproducible, and appropriate to your research question.[ 4 ]

In a typical clinical setting, a clinician needs to know about background and foreground questions depending upon the experience about a particular disease and therapy. Once background questions are answered, more complex questions are addressed. The clinical questions arise from the central issues in a clinical work.[ 2 ] For example, identifying causes or risk factors (etiological questions), comparing diagnostic tests based on sensitivity and specificity (diagnostic query), identifying best treatment options (therapeutic question), and outcome of the treatment (prognostic question).

After determining a foreground question, the PICO approach is followed. Dissecting the question into parts makes it easy and searchable. As evident in this case, there are several relevant questions, for example: what are the outcomes associated with recurrent ear infection, what are the possible effects of long-term use of antibiotic, and what are the harms associated with current treatment? Now if you gather all the information from PICO approach, the following researchable questions can be formulated.

In children with acute otitis media (P), is cefuroxime (I) effective in reducing the duration of symptoms (O) as compared to amoxicillin (C)?

In children suffering from otitis media, will cefuroxime result in the improvement of symptoms and reduction in developing resistance?

Does treatment with amoxicillin increase the risk of developing resistance in children suffering from otitis media?

Does surgical procedure has better outcome for the treatment of otitis media in children after repeated antibiotic therapy?

From the above case, we have formulated multiple questions based on our patient’s illness and concerns. Now we can use the strategy of “selecting” the best question.[ 2 ] For example, which question has more significance for the patient’s well-being, which question is relevant to our knowledge needs and which question might lead to interesting answers for our patients and clinical query? Further, we need to consider the feasibility of finding the evidence in a short period.

ASSESSING THE RESEARCH QUESTION IN THE CONTEXT OF A STUDY DESIGN

As proposed by Hulley et al . [ Table 1 ], a research question should be formulated keeping in mind the FINER (feasible, interesting, novel, ethical, and relevant) criteria[ 5 ] and that the answer should fill gaps in the existing knowledge. The following points should be considered while assessing a research question.

Determining the required resources

The feasibility of conducting a research project is based on the research question and should be considered early in the process in order to avoid waste of resources and intellectual energy. This is sometimes difficult for a new investigator and they need guidance from their mentors.[ 4 ]

• Consider doing a pilot or proof of concept study to asses the feasibility;
• Consult a biostatistician early in the project in order to choose less costly design and common outcomes;
• Consider feasibility of enrolling the intended number of subjects from the population of your interest. Also, consider expanding your inclusion criteria and modifying exclusion criteria if it is difficult to enroll the intended number; and
• Consider cost of each element of the study design, research staff, and resources.

Significance of making it interesting and relevant

An important question may not seem interesting the way it is presented. It is a challenge to present a research question clearly and engage the interest and attention of the reviewers. Research is too much work to not have a passion for what you are investigating. You will have more support for your study, and it will be easier to publish if the topic is novel and also interests your collaborators, colleagues, and the community at large. It is important to pursue a research question with a passion of getting the truth out of the matter.[ 5 ] This is how we all perceive research; commitment to a high-quality systematic and unbiased completion of an innovative project. If your question can explain a given problem while pointing toward a specific aspect which is missing then your project can get a great deal of support.

Conducting literature review

The innovation of any research question is determined by a thorough literature search. Any replication of the study already existing in the literature is not worth repeating as it is. Depending upon the research question, sometimes the study can be replicated if your question approaches an existing problem in a refreshing way. This can be achieved by using a different populations, different techniques, new conceptual approaches, or linking two different studies in which outcomes did not solve the problem.[ 5 ] Once a preliminary question has been formulated, literature search should be done to find out what is known or unknown about the topic. The goal of the literature review is to determine what research has been conducted on the topic of interest? and how has it been conducted? and what are the gaps in the knowledge?. It is recommended to use PubMed, MedlinePlus, CINAHL, or Web of Science as the main search databases, but other databases can be used as well. PubMed clinical query is an easy and user-friendly database to search for evidence related to clinical practice. This also provides information to search MEDLINE by doing categorical searches, for example, therapeutic, diagnostic, etiological, and prognostic. The American College of Physicians (ACP) and clinical evidence from BMJ Publishing Group are excellent systems to find evidence on therapeutic questions. Other search engines such as OVID has a large selection of texts and journals which provides access to other databases such as Cochrane library in getting full text articles and systematic reviews. Gray et al . suggested 4 Ss for literature review: Systems : use of comprehensive resources, Synopses : extracting high-quality studies and abstracts, Syntheses: systematic reviews, and Studies : original research studies.[ 6 ] In the hierarchy of evidence-based medicine, systematic reviews are considered the best method for evidence. Systematic reviews are rigorous methods of collecting and synthesizing the results of many high-quality studies. Conducting a thorough literature search also helps in finding information on the methodology, calculating the sample size, and also the type of analysis as we are looking to find a difference. This information is necessary to help structure a new study and to identify gaps in the knowledge base of the scientific community.

Refining research question

A focused research question leads to a systematic planning of a research project. The difficulty in framing a research question is not due to the lack of ideas. The challenge is to transform a novel research question into a valid study design which is the next step in refining a research question.

Asking a well-formulated research question is a starting point in conducting a quality research project and in evidence-based clinical practice. The framework presented in this paper can be helpful for a clinician to formulate a question and search for an answer and for a researcher to develop a new research project. The classical approach is to identify a research question followed by a thorough literature search keeping in mind the PICO and FINER criteria. If it is a well-defined research question, it will lead to an appropriate study design and methodology. Discussing your research question with knowledgeable peers, department chair, mentor, and the biostatistician from the start will lead to the completion of a successful project. Other steps such as type and phase of the clinical trial, budget, informed consent, sites, resource constraints of both personnel and facilities, and timeline should also be considered while formulating a research question. We have introduced the concept of background and foreground questions and also the types of different questions that can arise (therapy, harm, diagnosis, and prognosis). We have described several strategies here while highlighting the major steps that will help investigators in framing a question with the goal of finding an answer based on evidence or initiation of a new research project. It is always good to focus on a single research question based on its relevance to patient’s health or one primary objective to drive the study design.[ 4 ] Once we have formulated our research question, we need to keep track of the progress toward finding an appropriate answer and then finally applying the results to a specific patient population. In short, a researchable question is what leads toward the facts rather than opinion[ 7 ] and is clearly linked to the overall research project goal.

Acknowledgments

The authors would like to acknowledge Dr. J.K Kosambiya, Dr. Eknath Naik, and Dr. Ambuj Kumar for their time in reviewing the paper and providing useful insights.

Source of Support: Nil

Conflict of Interest: None declared.

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• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

• Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

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As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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Online Guide to Writing and Research

The research process, explore more of umgc.

• Online Guide to Writing

Planning and Writing a Research Paper

Ask a Research Question

When we perform research, we enter the community of scholars who, before us, sought to answer questions for themselves and others. We set out on a journey of discovery that draws us into the ongoing conversation about that subject matter. This is also your opportunity to add your voice to the scholarly work that has already been written about your topic.    

BEGIN WITH A QUESTION

As you dive into the scholarly conversation about your topic, you need to begin with a question that you are going to answer in your paper.  To begin this process, you need to brainstorm some ideas that interest you. You can brainstorm with a classmate or coworker or even ask your professor for suggestions, but the question you generate is the one you will be invested in answering. 

KEEP THE SCOPE MANAGEABLE

As you explore the research question you want to answer, keep in mind that your question and research should be sized to fit the assignment you have been given. Keep the scope of your research manageable. Ask a question that will lead you into your research—a specific, concrete question that will help you devise a working thesis and give you direction for your information search. Generally, the answer to your question should take a stance. 

TEST YOUR RESEARCH QUERY

When you have tentatively decided on your research question and have a working thesis, answer these questions to test your research inquiry:

Is the scope of the question appropriate for the assignment?

Is my question specific enough so that I know what I'm looking for? Or is my question too broad or too narrow?

Can I find enough information on the subject?

• Will the answer to my question take a specific stance on the topic?
• Do I really care about finding the answers to my question?
• Does my answer result in more than a "yes" or "no" answer?

When the answers to these questions are yes, you are ready to research in more depth and manage your research resources.

Key Takeaways

• The answer to your research question will eventually be your thesis statement, which will take a stance. 
• Frame your research question so that it does not result in a "yes" or "no" answer, but an in-depth answer. 

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Table of Contents: Online Guide to Writing

Chapter 1: College Writing

How Does College Writing Differ from Workplace Writing?

What Is College Writing?

Why So Much Emphasis on Writing?

Chapter 2: The Writing Process

Doing Exploratory Research

Getting from Notes to Your Draft

Introduction

Prewriting - Techniques to Get Started - Mining Your Intuition

Prewriting: Targeting Your Audience

Prewriting: Techniques to Get Started

Prewriting: Understanding Your Assignment

Rewriting: Being Your Own Critic

Rewriting: Creating a Revision Strategy

Rewriting: Getting Feedback

Rewriting: The Final Draft

Techniques to Get Started - Outlining

Techniques to Get Started - Using Systematic Techniques

Thesis Statement and Controlling Idea

Writing: Getting from Notes to Your Draft - Freewriting

Writing: Getting from Notes to Your Draft - Summarizing Your Ideas

Writing: Outlining What You Will Write

Chapter 3: Thinking Strategies

A Word About Style, Voice, and Tone

A Word About Style, Voice, and Tone: Style Through Vocabulary and Diction

Critical Strategies and Writing

Critical Strategies and Writing: Analysis

Critical Strategies and Writing: Evaluation

Critical Strategies and Writing: Persuasion

Critical Strategies and Writing: Synthesis

Developing a Paper Using Strategies

Kinds of Assignments You Will Write

Patterns for Presenting Information

Patterns for Presenting Information: Critiques

Patterns for Presenting Information: Discussing Raw Data

Patterns for Presenting Information: General-to-Specific Pattern

Patterns for Presenting Information: Problem-Cause-Solution Pattern

Patterns for Presenting Information: Specific-to-General Pattern

Patterns for Presenting Information: Summaries and Abstracts

Supporting with Research and Examples

Writing Essay Examinations

Writing Essay Examinations: Make Your Answer Relevant and Complete

Writing Essay Examinations: Organize Thinking Before Writing

Writing Essay Examinations: Read and Understand the Question

Chapter 4: The Research Process

Planning and Writing a Research Paper: Ask a Research Question

Planning and Writing a Research Paper: Cite Sources

Planning and Writing a Research Paper: Collect Evidence

Planning and Writing a Research Paper: Decide Your Point of View, or Role, for Your Research

Planning and Writing a Research Paper: Draw Conclusions

Planning and Writing a Research Paper: Find a Topic and Get an Overview

Planning and Writing a Research Paper: Manage Your Resources

Planning and Writing a Research Paper: Outline

Planning and Writing a Research Paper: Survey the Literature

Planning and Writing a Research Paper: Work Your Sources into Your Research Writing

Research Resources: Where Are Research Resources Found? - Human Resources

Research Resources: What Are Research Resources?

Research Resources: Where Are Research Resources Found?

Research Resources: Where Are Research Resources Found? - Electronic Resources

Research Resources: Where Are Research Resources Found? - Print Resources

Structuring the Research Paper: Formal Research Structure

Structuring the Research Paper: Informal Research Structure

The Nature of Research

The Research Assignment: How Should Research Sources Be Evaluated?

The Research Assignment: When Is Research Needed?

The Research Assignment: Why Perform Research?

Chapter 5: Academic Integrity

Academic Integrity

Giving Credit to Sources

Giving Credit to Sources: Copyright Laws

Giving Credit to Sources: Documentation

Giving Credit to Sources: Style Guides

Integrating Sources

Practicing Academic Integrity

Practicing Academic Integrity: Keeping Accurate Records

Practicing Academic Integrity: Managing Source Material

Practicing Academic Integrity: Managing Source Material - Paraphrasing Your Source

Practicing Academic Integrity: Managing Source Material - Quoting Your Source

Practicing Academic Integrity: Managing Source Material - Summarizing Your Sources

Types of Documentation

Types of Documentation: Bibliographies and Source Lists

Types of Documentation: Citing World Wide Web Sources

Types of Documentation: In-Text or Parenthetical Citations

Types of Documentation: In-Text or Parenthetical Citations - APA Style

Types of Documentation: In-Text or Parenthetical Citations - CSE/CBE Style

Types of Documentation: In-Text or Parenthetical Citations - Chicago Style

Types of Documentation: In-Text or Parenthetical Citations - MLA Style

Types of Documentation: Note Citations

Chapter 6: Using Library Resources

Finding Library Resources

Chapter 7: Assessing Your Writing

How Is Writing Graded?

How Is Writing Graded?: A General Assessment Tool

The Draft Stage

The Draft Stage: The First Draft

The Draft Stage: The Revision Process and the Final Draft

The Draft Stage: Using Feedback

The Research Stage

Using Assessment to Improve Your Writing

Chapter 8: Other Frequently Assigned Papers

Reviews and Reaction Papers: Article and Book Reviews

Reviews and Reaction Papers: Reaction Papers

Writing Arguments

Writing Arguments: Adapting the Argument Structure

Writing Arguments: Purposes of Argument

Writing Arguments: References to Consult for Writing Arguments

Writing Arguments: Steps to Writing an Argument - Anticipate Active Opposition

Writing Arguments: Steps to Writing an Argument - Determine Your Organization

Writing Arguments: Steps to Writing an Argument - Develop Your Argument

Writing Arguments: Steps to Writing an Argument - Introduce Your Argument

Writing Arguments: Steps to Writing an Argument - State Your Thesis or Proposition

Writing Arguments: Steps to Writing an Argument - Write Your Conclusion

Writing Arguments: Types of Argument

Appendix A: Books to Help Improve Your Writing

Dictionaries

General Style Manuals

Researching on the Internet

Special Style Manuals

Writing Handbooks

Appendix B: Collaborative Writing and Peer Reviewing

Collaborative Writing: Assignments to Accompany the Group Project

Collaborative Writing: Informal Progress Report

Collaborative Writing: Issues to Resolve

Collaborative Writing: Methodology

Collaborative Writing: Peer Evaluation

Collaborative Writing: Tasks of Collaborative Writing Group Members

Collaborative Writing: Writing Plan

General Introduction

Peer Reviewing

Appendix C: Developing an Improvement Plan

Working with Your Instructor’s Comments and Grades

Appendix D: Writing Plan and Project Schedule

Devising a Writing Project Plan and Schedule

Reviewing Your Plan with Others

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Think Like a Researcher: Instruction Resources: #6 Developing Successful Research Questions

• Guide Organization
• Overall Summary
• #1 Think Like a Researcher!
• #2 How to Read a Scholarly Article
• #3 Reading for Keywords (CREDO)
• #4 Using Google for Academic Research
• #4 Using Google for Academic Research (Alternate)
• #5 Integrating Sources
• Research Question Discussion
• #7 Avoiding Researcher Bias
• #8 Understanding the Information Cycle
• #9 Exploring Databases
• #10 Library Session
• #11 Post Library Session Activities
• Summary - Readings
• Summary - Research Journal Prompts
• Summary - Key Assignments
• Jigsaw Readings
• Permission Form

Course Learning Outcome:   Develop ability to synthesize and express complex ideas; demonstrate information literacy and be able to work with evidence

Goal:  Develop students’ ability to recognize and create successful research questions

Specifically, students will be able to

• identify the components of a successful research question.
• create a viable research question.

What Makes a Good Research Topic Handout

These handouts are intended to be used as a discussion generator that will help students develop a solid research topic or question. Many students start with topics that are poorly articulated, too broad, unarguable, or are socially insignificant. Each of these problems may result in a topic that is virtually un-researchable. Starting with a researchable topic is critical to writing an effective paper.

Research shows that students are much more invested in writing when they are able to choose their own topics. However, there is also research to support the notion that students are completely overwhelmed and frustrated when they are given complete freedom to write about whatever they choose. Providing some structure or topic themes that allow students to make bounded choices may be a way mitigate these competing realities.

These handouts can be modified or edited for your purposes.  One can be used as a handout for students while the other can serve as a sample answer key.  The document is best used as part of a process.  For instance, perhaps starting with discussing the issues and potential research questions, moving on to problems and social significance but returning to proposals/solutions at a later date.

• Research Questions - Handout Key (2 pgs) This document is a condensed version of "What Makes a Good Research Topic". It serves as a key.
• Research Questions - Handout for Students (2 pgs) This document could be used with a class to discuss sample research questions (are they suitable?) and to have them start thinking about problems, social significance, and solutions for additional sample research questions.
• Research Question Discussion This tab includes materials for introduction students to research question criteria for a problem/solution essay.

Additional Resources

These documents have similarities to those above.  They represent original documents and conversations about research questions from previous TRAIL trainings.

• What Makes a Good Research Topic? - Original Handout (4 pgs)
• What Makes a Good Research Topic? Revised Jan. 2016 (4 pgs)
• What Makes a Good Research Topic? Revised Jan 2016 with comments

Topic Selection (NCSU Libraries)

Howard, Rebecca Moore, Tricia Serviss, and Tanya K. Rodrigues. " Writing from sources, writing from sentences ." Writing & Pedagogy 2.2 (2010): 177-192.

Research Journal

Assign after students have participated in the Developing Successful Research Topics/Questions Lesson OR have drafted a Research Proposal.

Think about your potential research question.

• What is the problem that underlies your question?
• Is the problem of social significance? Explain.
• Is your proposed solution to the problem feasible? Explain.
• Do you think there is evidence to support your solution?

Keys for Writers - Additional Resource

Keys for Writers (Raimes and Miller-Cochran) includes a section to guide students in the formation of an arguable claim (thesis).  The authors advise students to avoid the following since they are not debatable. 

• "a neutral statement, which gives no hint of the writer's position"
• "an announcement of the paper's broad subject"
• "a fact, which is not arguable"
• "a truism (statement that is obviously true)"
• "a personal or religious conviction that cannot be logically debated"
• "an opinion based only on your feelings"
• "a sweeping generalization" (Section 4C, pg. 52)

The book also provides examples and key points (pg. 53) for a good working thesis.

• << Previous: #5 Integrating Sources
• Next: Research Question Discussion >>
• Last Updated: Apr 26, 2024 10:23 AM
• URL: https://libguides.ucmerced.edu/think_like_a_researcher

Project Planning for the Beginner: Developing a Researchable Question

• Defining a Topic
• Reviewing the Literature
• Developing a Researchable Question
• Research Design
• Planning, Data, Writing and Dissemination

How Do I Develop a Research Question?

Here are four possible approaches to developing your research question(s). These are not mutually exclusive.

You may hope to work on a general description of a social context. Often, descriptive ethnography takes this form. However, you need to focus on particular aspects of that context which are especially interesting and which result in an understanding which can be generalized beyond the particular context of your research.

You may wish to test a hypothesis . This means you have constructed a specifically formulated statement which can be falsified. This is the dominant approach in experimental research . Usually you will employ statistical methods to test a null hypothesis , which asserts the opposite of the proposition you are testing.

If, for example, your hypothesis is that there is a difference in political attitudes among the people of different ethnic backgrounds in a specific country, you might look at a sample of survey data to test this. In this case, the null hypothesis is that no difference in political attitudes can be found.

You may have some developed ideas about what you wish to engage with, but not a formal testable hypothesis.

Alternatively, your methodological approach may be based on grounded theory . You do not have a hypothesis that you wish to test, but rather you will work in context and the important questions will emerge as you interact systematically with the data you generate from your research. 

Crafting Your Research Questions

Types of research questions: why when who how where.

When developing and answering your research questions, you should be aware of the specific usage of these words in a social science context. “Why” questions seek causal explanations. If you ask “why?” the answer begins with “because.”

When questions locate:

• Events in relation to the time at which they happened

• Processes in relation to when they happened and their duration

• The setting of things in temporal order, or sequencing

• Boundaries of the context of your research.

These last two types of “when” questions have implications for causality and for the generalizations you may be able to make from your research.

Who questions address agency. They seek to identify the persons, institutions, or collective bodies responsible for the things you are researching. You may use who questions simply to identify an informant: “Who told me this?” But you may also use them to indicate specific agency as the cause of an event.

How questions are about mechanisms. The answers describe ways in which things are done, which together result in a given outcome. These questions might cover:

• How you carry out your own research.

• The accounts you generate from your research to indicate how something happened.

Note that there is overlap between how and why questions when dealing with events or system states. Both are addressing cause. Where questions (like when questions) set your research in context. It is important to understand the social world in terms of contextual spaces and circumstances. Both where and when questions should generate answers which help you define the extent to which you can generalize the results of your research. 

What Kinds of Change Can My Research Identify?

Much of social research is concerned with change. In experiments and action research we try to create change. In observational studies we try to see what change has happened. Sometimes, of course, we are interested in why things stay the same.

Here are some examples of the types of change you might identify:

• Changes of kind : Most social science disciplines are concerned with changes of kind. We are interested in the way things become different in terms of the kind of things they are.

• Changes of degree : Some social science is concerned with changes of degree. For example, we may do research on changes in educational achievement.

Identifying change always involves some sort of measurement , even if that measurement is implicit.

• Taxonomies : Social scientists—and other scientists—use classifications to describe different systems. We would do this to identify changes in kind. This process involves the construction of taxonomies, which are systematic sets of types of entities.

• Continuous scales of measurement: To assess changes of degree, we use continuous scales of measurement. For example, we would use a scoring system to measure changes in educational achievement. 

What Makes a Researchable Question?

Here are seven questions to ask yourself. Remember, it’s possible that not all will apply to you. 

• Do I know enough about the area I’m working in to formulate one or more interesting questions which relate to current issues or debates? 
• Do I know which methods I am going to use in my research? If not, see Sage Research Methods "Which Methods Should I Use?"
• Do I have the necessary competence in these methods? If not, can I acquire it in time to do this research?
• Do I have the resources I need: equipment, office space, materials, support?
• Can I get access to the research field?
• Do I have the time needed to complete the work using the methods I’ve identified?
• Do I have time to analyze my research findings, write them up coherently, and draw the project to a conclusion?

Developing a Research Question

• << Previous: Reviewing the Literature
• Next: Research Design >>
• Last Updated: May 11, 2022 2:56 PM
• URL: https://libguides.sph.uth.tmc.edu/c.php?g=949457

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Is the U.S. economy finally cooling? While it will take several months of data to answer that question, one key piece of the puzzle comes with the closely watched employment report. Here with more on this is our Chief Equity Strategist and Economist, John Blank.

1. We had an employment report out recently in earlyJune. Did that help answer this question?

2. We’ll have the next employment report come out on Friday July 5 th . Do you expect that to provide any further clarity on this question?

3. We’ve seen a lot of economic data recently. Does that support a cooling scenario?

4. The main economic event though has investors looking ahead to tomorrow’s PCE report for clues about possible Federal Reserve rate cuts. Are you hopeful for a rate cut this year yet?

5. We saw consumer spending soften a bit in April and retail sales increased less than expected in May. Does that indicate lackluster GDP growth going forward?

6. You view the housing market as a key economic indicator. First we had a lack of inventory. But now published data shows home listings staring to rise but the home buyers are slow to show up. Is higher for longer rates choking off demand? If so, how concerning is that?

7. Where then are the bright spots in the macro economic landscape currently?

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Published on 25.6.2024 in Vol 26 (2024)

Potential Roles of Large Language Models in the Production of Systematic Reviews and Meta-Analyses

Authors of this article:

• Xufei Luo 1, 2, 3, 4, 5   ; 
• Fengxian Chen 6 , PhD   ; 
• Di Zhu 7 , MPH   ; 
• Ling Wang 7 , MPH   ; 
• Zijun Wang 1, 2, 3, 4, 5   ; 
• Hui Liu 1, 2, 3, 4, 5   ; 
• Meng Lyu 7 , MPH   ; 
• Ye Wang 7 , MPH   ; 
• Qi Wang 8, 9 , PhD   ; 
• Yaolong Chen 1, 2, 3, 4, 5 , MD, PhD  

1 Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China

2 World Health Organization Collaboration Center for Guideline Implementation and Knowledge Translation, Lanzhou, China

3 Institute of Health Data Science, Lanzhou University, Lanzhou, China

4 Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou University, Lanzhou, China

5 Research Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, China

6 School of Information Science & Engineering, Lanzhou University, Lanzhou, China

7 School of Public Health, Lanzhou University, Lanzhou, China

8 Department of Health Research Methods, Evidence and Impact, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada

9 McMaster Health Forum, McMaster University, Hamilton, ON, Canada

Corresponding Author:

Yaolong Chen, MD, PhD

Evidence-Based Medicine Center

School of Basic Medical Sciences

Lanzhou University

No 199 Donggang West Road

Chengguan District

Lanzhou, 730000

Phone: 86 13893104140

Email: [email protected]

Large language models (LLMs) such as ChatGPT have become widely applied in the field of medical research. In the process of conducting systematic reviews, similar tools can be used to expedite various steps, including defining clinical questions, performing the literature search, document screening, information extraction, and language refinement, thereby conserving resources and enhancing efficiency. However, when using LLMs, attention should be paid to transparent reporting, distinguishing between genuine and false content, and avoiding academic misconduct. In this viewpoint, we highlight the potential roles of LLMs in the creation of systematic reviews and meta-analyses, elucidating their advantages, limitations, and future research directions, aiming to provide insights and guidance for authors planning systematic reviews and meta-analyses.

Introduction

A systematic review is the result of a systematic and rigorous evaluation of evidence, which may or may not include a meta-analysis [ 1 ]. Owing to the strict methodology and comprehensive summary of evidence, high-quality systematic reviews are considered the highest level of evidence, positioned at the top of the evidence pyramid [ 2 ]. Additionally, high-quality systematic reviews and meta-analyses are often used to support the development of clinical practice guidelines, aid clinical decision-making, and inform health care policy formulation [ 3 ]. Currently, the methods of systematic reviews and meta-analyses are applied in various disciplines in medicine and beyond such as law [ 4 ], management [ 5 ], and economics [ 6 ], and have yielded positive results, contributing to the continuous advancement of these fields [ 7 ].

The process of conducting systematic reviews demands a substantial investment in terms of time, resources, human effort, and financial capital [ 8 ]. To expedite the development of systematic reviews and meta-analyses, various automated or semiautomated tools such as Covidence have been developed [ 9 , 10 ]. However, the emergence of large language models (LLMs), particularly chatbots such as GPT, presents a set of both challenges and opportunities in the realm of systematic reviews and meta-analyses [ 11 ]. Based on the emerging literature in this field, we here provide our perspectives on the potential for harnessing the capabilities of LLMs to accelerate the production of systematic reviews and meta-analyses, while also scrutinizing the potential impacts and delineating the crucial steps involved in this process.

The Process and Challenges of Performing a Systematic Review and Meta-Analysis

The procedures and workflows for conducting systematic reviews and meta-analyses are well-established. Currently, researchers often refer to the Cochrane Handbooks recommended by the Cochrane Library for intervention or diagnostic reviews [ 12 , 13 ]. In addition, some scholars and institutions have developed detailed guidelines on the steps and methodology for performing systematic reviews and meta-analyses [ 14 - 17 ]. Generally speaking, researchers should take the following steps to produce a high-quality systematic review and meta-analysis: determine the clinical question, register and draft a protocol, set inclusion and exclusion criteria, develop and implement a search strategy, screen the literature, extract data from included studies, assess the quality and risk of bias of included studies, analyze and processed data, write up the full text of the manuscript, and submit the manuscript for publication, as illustrated in Figure 1 . These different steps contain many subtasks; therefore, conducting a complete systematic review and meta-analysis requires fairly complex and time-consuming work.

Although systematic reviews and meta-analyses have been widely applied and play an important role in developing guidelines and informing clinical decision-making, their production process faces many challenges. One of these challenges is the long production time and large resource requirements. The average estimated time to complete and publish a systematic review is 67.3 weeks, requiring 5 researchers and costing approximately US $140,000 [ 18 , 19 ]. More recently, the development of automated and semiautomated tools using natural language processing and machine learning have accelerated systematic review and meta-analysis production to some extent [ 20 ], with studies showing that such tools can help to produce a systematic review and meta-analysis within 2 weeks [ 21 ]. However, these tools also have some limitations. First, no single tool can fully accelerate the entire production process of systematic reviews and meta-analyses. Second, these tools cannot process and analyze literature written in different languages. Finally, the reliability of the results generated by these automated and semiautomated tools needs further validation as they are not yet widely adopted for this purpose.

Applications of LLMs in Medical Research

Chatbots based on LLMs such as ChatGPT, Google Gemini, and Claude have become widely applied in medical research. These chatbots have proven to be valuable in tasks ranging from knowledge retrieval, language refinement, content generation, and medical exam preparation to literature assessment. ChatGPT has been shown to excel in accuracy, completeness, nuance, and speed when generating responses to clinical inquiries in psychiatry [ 22 ]. Moreover, LLMs such as ChatGPT play a pivotal role in automating the evaluation of medical literature, facilitating the identification of accurately reported research findings [ 23 ]. Despite their significant contributions, these chatbots are not without limitations. Challenges such as the potential for generating misleading content and susceptibility to academic deception necessitate further scholarly discourse on effective mitigation strategies. Standardized reporting practices may contribute to delineating the applications of ChatGPT and mitigating research biases [ 24 ].

ChatGPT has also demonstrated significant application potential and promise in the process of conducting systematic reviews and meta-analyses. Various studies [ 11 , 25 - 32 ] indicate that ChatGPT can play a pivotal role in formulating clinical questions, determining inclusion and exclusion criteria, screening literature, assessing publications, generating meta-analysis code, and assisting the full-text composition, among other relevant tasks. The details of these capabilities are summarized in Table 1 .

Potential Roles of LLMs in Producing Systematic Reviews and Meta-Analyses

Determine the research topic/question.

Determining the clinical question of interest represents the initial and paramount step in the process of conducting systematic reviews and meta-analyses. At this juncture, it is crucial to ascertain whether comparable systematic reviews and meta-analyses have already been published and to delineate the scope of the forthcoming review and meta-analysis. Generally, for interventional systematic reviews, the Patient, Intervention, Comparison, and Outcome (PICO) framework is considered for defining the scope and objectives of the research question [ 60 ]. In this context, ChatGPT serves a dual role. On the one hand, it expeditiously aids in searching for published systematic reviews and meta-analyses related to the relevant topics (see Multimedia Appendix 1 and Multimedia Appendix 2 ) [ 34 ]. On the other hand, ChatGPT assists in refining the clinical question that needs to be addressed (see Multimedia Appendix 3 ), facilitating prompt determination of the feasibility of undertaking the proposed study. However, it is important to be cautious of the retrieval of false literature [ 35 ].

Register and Write a Research Proposal

The registration and proposal writing process constitutes a pivotal preparatory phase for conducting systematic reviews and meta-analyses. Registration enhances research transparency, fosters collaboration among investigators, and mitigates the redundancy of research endeavors. Drafting a proposal helps in elucidating the research objectives and methods, providing robust support for the smooth execution of the study. For LLMs, generating preliminary registration information and initial proposal content is remarkably convenient and facile (see Multimedia Appendix 4 and Multimedia Appendix 5 ). For example, ChatGPT can assist researchers in generating the statistical methods for a research proposal [ 37 ]. However, considering that LLMs often generate fictitious literature, the content they produce may be inaccurate; thus, discernment and validation of the generated content remain essential considerations.

Define Inclusion and Exclusion Criteria

The inclusion and exclusion criteria for systematic reviews and meta-analyses are instrumental in determining the screening standards for studies. Therefore, strict and detailed inclusion and exclusion criteria contribute to the smooth and high-quality conduct of preparing systematic reviews and meta-analyses. The use of a chatbot based on LLMs can help in establishing the inclusion and exclusion criteria (see Multimedia Appendix 6 ) [ 38 ]; however, the inclusion criteria need to be optimized and adjusted according to the specific research objectives and the exclusion criteria should be based on the foundation of the inclusion criteria. Therefore, manual adjustments and optimizations are also necessary.

Develop a Search Strategy and Conduct Searches

ChatGPT can assist in formulating search strategies, using PubMed as an example [ 40 ]. Researchers can simply list their questions using the PICO framework and a search strategy can be quickly generated ( Multimedia Appendix 1 and Multimedia Appendix 2 ). Based on the generated search strategy, one method is to copy the strategy from ChatGPT and paste it into the PubMed search box for direct retrieval [ 40 , 41 ]. Another approach involves using the OpenAI application programming interfaces (APIs) to invoke PubMed APIs with the search strategy generated by ChatGPT. This facilitates searching the PubMed database, obtaining search results, and applying predetermined inclusion and exclusion criteria. Subsequently, ChatGPT can be used to filter the search results, exporting and recording the filtered results in JSON format. This integrated process encompasses search strategy formulation, retrieval, and filtering. However, the direct use of LLMs to generate search strategies and complete the one-stop process of searching and screening may not yet be mature, and this poses a significant challenge for generating the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) flowchart. Therefore, we suggest using LLMs to generate search strategies, which should then be optimized and modified by librarians and computer experts (specializing in LLMs) before manually searching the databases. Additionally, to use search strategies transparently and reproducibly, the detailed prompts used should be reported [ 40 , 42 ].

Screen the Literature

Literature screening is one of the most time-consuming steps in the creation of systematic reviews and meta-analyses. Prior to the advent of ChatGPT, there were already many automated and semiautomated tools available for literature screening, such as Covidence, EPPI-Reviewer, DistillerSR, and others [ 39 ]. With the emergence of ChatGPT, researchers can now train the model based on predefined inclusion criteria. Subsequently, ChatGPT can be used to automatically screen records retrieved from databases and obtain the filtered results. Previous studies suggested that using ChatGPT in the literature selection process for a meta-analysis substantially diminishes the workload while preserving a recall rate on par with that of manual curation [ 28 , 44 - 47 ].

Extract the Data

Data extraction involves obtaining information from primary studies and serves as a primary source for systematic reviews and meta-analyses. Generally, when conducting systematic reviews and meta-analyses, basic information must be extracted from the original studies, such as publication date, country of conduct, and the journal of publication. Additionally, characteristics of the population, such as patient samples, age, gender/sex, and outcome data, are also extracted, including event occurrences, mean change values, and total sample size. Currently, tools based on natural language processing and LLMs, such as ChatGPT and Claude, demonstrate high accuracy in extracting information from PDF documents (see Multimedia Appendix 7 for an example) [ 47 - 50 ]. However, it is important to note that despite their promising capabilities, manual verification remains a necessary step in the data extraction process when using these artificial intelligence (AI) tools [ 61 ]. Using LLMs to extract data can help avoid random errors; however, caution is still required when extracting data from figures or tables [ 47 - 50 ].

Assess the Risk of Bias

Assessing the bias of risk involves evaluating the internal validity of studies included in research. For randomized controlled trials, tools such as Risk of Bias (RoB) [ 62 ] or its updated version RoB 2 [ 63 ] are typically used, with an estimated review time of 10-15 minutes per trial. However, automated tools such as RobotReviewer can streamline the extraction and evaluation process in batches [ 51 - 53 ], thereby improving efficiency, although manual verification is still necessary. Additionally, chatbots based on LLMs can aid in risk of bias assessment (see Multimedia Appendix 8 ), and their accuracy appears to be comparable to that of human evaluations [ 23 ].

Analyze the Data/Meta-Analysis

Data analysis serves as the source of systematic review results, typically encompassing basic information and outcome findings. The meta-analysis may be one outcome, along with potential components such as subgroup analysis, sensitivity analysis, meta-regression, and detection of publication bias. Numerous software options are available to facilitate these data analyses, including Stata, RevMan, Rstudio, and others [ 43 ]. Currently, it appears that chatbots based on LLMs may not fully execute data analysis independently, although they can extract the relevant information. Subsequently, one can employ corresponding software for comprehensive data analysis. Alternatively, after extracting information with chatbots, the ChatGPT Code Interpreter can assist in analysis and generating graphical results, although this requires a subscription to ChatGPT Plus. Moreover, an LLM markedly accelerates the data analysis process, empowering researchers to handle larger data sets with greater efficacy [ 54 ].

Draft the Full Manuscript

The complete drafting of systematic reviews and meta-analyses should adhere to the PRISMA reporting guidelines [ 64 ]. It is not advisable to use chatbots such as ChatGPT for article composition. On the one hand, the accuracy and integrity of content generated by ChatGPT require human verification. On the other hand, various research types and journals have different requirements for full-length articles, making it challenging to achieve uniformity in the generated content. However, using tools such as GPT for language refinement and adjusting the content logic can be considered to enhance the quality and readability of the article [ 33 , 55 ]. It is important to declare the use of GPT-related tools in the methods, acknowledgments, or appendices of the article to ensure transparency [ 24 , 65 ].

Submit and Publish

Submission and publication represent the final steps in the process of conducting systematic reviews and meta-analyses, aside from subsequent updates. At this stage, the potential role of LLM-based tools is to assist authors in recommending suitable journals (see Multimedia Appendix 9 ). These tools might also aid in crafting components required along with submission of the manuscript such as cover letters and highlights [ 59 ]. However, it is imperative to emphasize that the content generated by these tools requires manual verification to ensure accuracy, and all authors should be accountable for the content generated by LLMs.

Benefits and Drawbacks of Using LLMs

Systematic reviews and meta-analyses are crucial evidence types that support the development of guidelines [ 3 ]. The benefits of employing LLM-based chatbots in the production of systematic reviews and meta-analyses include increased speed, such as in the stages of evidence searching, data extraction, and assessment of bias risk; these tools can also enhance accuracy by reducing human errors such as those made while extracting essential information and pooling data. However, there are also drawbacks of these applications of LLMs, such as the potential for generating hallucinations, the requirement for human verification owing to the poor reliability of the models, and that the entire systematic review process is not replicable. Moreover, when interacting with LLM chatbots, it is important to manage data privacy. In particular, when using LLMs to analyze data, especially when including personal patient information, ethical approval and management must be properly addressed.

Challenges and Solutions

While LLMs can assist in accelerating the production of systematic reviews and meta-analyses in some steps, enhancing accuracy and transparency, and saving resources, they also face several challenges. For instance, LLMs cannot promptly update their versions and information. For example, ChatGPT 3.5 has been trained on data available in 2021. Thus, limitations such as the length of prompts and token constraints, as well as restrictions related to context associations, may potentially impact the overall results and user experience [ 25 ]. Although LLM-based autonomous agents have made strides in tasks related to systematic reviews and meta-analyses, their applications are still associated with various issues related to personalization, updating knowledge, strategic planning, and complex problem-solving. The development of LLM-driven autonomous agents adept at systematic reviews and meta-analyses warrants further exploration [ 66 ]. The use of LLMs as centrally controlled intelligent agents encompasses the ability to handle precise literature screening, extract and analyze complex data, and assist in manuscript composition, as highlighted by proof-of-concept demonstrations such as MetaGPT [ 67 ]. Moreover, the continuous growth of the use of LLMs can pose a significant challenge in ensuring the accuracy of information provided in systematic reviews, particularly if LLMs are indiscriminately overused.

To better facilitate the use of tools such as ChatGPT in systematic reviews and meta-analyses, we believe that, first and foremost, authors should understand the scope and scenarios for applying ChatGPT, clearly defining which steps can benefit from these tools. Second, for researchers, collaboration with computer scientists and AI engineers is crucial to optimize the prompts and develop integrated tools based on LLMs, such as web applications. These tools can assist in seamless transitions between different tasks in the systematic review process. Lastly, for journal editors, collaboration with authors and reviewers is essential to adhere to reporting and ethical principles associated with the use of GPT and similar tools [ 24 , 68 ]. This collaboration aims to promote transparency and integrity, while preventing indiscriminate overuse in the application of LLMs in systematic reviews and meta-analyses.

Future Perspectives and Conclusion

The emergence of LLMs could have a significant impact on the production of systematic reviews and meta-analyses. In this process, the application of chatbots such as ChatGPT has the potential to speed up certain steps such as literature screening, data extraction, and risk of bias assessment, which are processes that typically consume a considerable amount of time. However, it is important to note that if AI methods such as GPT are employed in performing systematic reviews, disclosure and declaration of the use of these tools are essential. This includes specifying the AI tools used, their roles, and the areas of application within the review process, among other relevant information for full disclosure [ 24 ]. In this context, developing a reporting guideline is warranted to guide the application of LLM tools in systematic reviews and meta-analyses. Although the PRISMA 2020 guideline briefly addresses the use of automation technologies, its coverage is limited to steps such as screening, and there is a lack of comprehensive guidance on the broader spectrum of applications [ 64 ].

Acknowledgments

ChatGPT 3.5 designed by OpenAI was used to help with language editing. The authors take the ultimate responsibility for the content of this publication.

Authors' Contributions

XL and YC were responsible for conceptualization of the article. XL, FC, DZ, and LW generated the examples with the large language models and wrote the first draft of the article. XL, ZW, HL, ML, YW, QW, and YC reviewed and edited the manuscript. YC supervised the study, takes full responsibility for the work and conduct of the study, has access to the data, and controlled the decision to publish. All authors read the final manuscript and approved the submission.

Conflicts of Interest

None declared.

Using ChatGPT 4.0 to assist in generating PubMed search strategies for assessing systematic reviews.

The results obtained after searching the PubMed database based on the search strategy generated by ChatGPT.

Using ChatGPT 4.0 to assist in optimizing the clinical question for conducting a systematic review and meta-analysis.

Using ChatGPT 4 to generate PROSPERO (International Prospective Register of Systematic Reviews) registration information.

Proposal of a systematic review and meta-analysis related to exercises for osteoarthritis generated by Claude 3 based on the provided prompts.

The inclusion and exclusion criteria for a systematic review and meta-analysis on exercise therapy for osteoarthritis based on GPT-4.

Using Claude 3 for data extraction from PDF documents: an example with three randomized controlled trials.

Using Claude 3 for risk of bias assessment: an example with two randomized controlled trials.

Using GPT-4 to assist in selecting target journals for submission of a systematic review and meta-analysis.

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Abbreviations

Edited by G Eysenbach; submitted 20.02.24; peer-reviewed by A Jafarizadeh, M Chatzimina, AS Van Epps; comments to author 03.05.24; revised version received 21.05.24; accepted 29.05.24; published 25.06.24.

©Xufei Luo, Fengxian Chen, Di Zhu, Ling Wang, Zijun Wang, Hui Liu, Meng Lyu, Ye Wang, Qi Wang, Yaolong Chen. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 25.06.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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Short-Term Residential Rentals Study

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‘Home sharing’ (or short-term residential rentals) refers to the rental of houses, condos, or apartments to short-term guests, which has become a popular way for owners to earn extra income across the United States. Short-term residential rentals typically occur through online home-sharing platforms, such as Airbnb, Expedia, FlipKey, HomeAway, TripAdvisor, and VRBO.  

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In 2017, the Virginia General Assembly adopted a law that allows a locality to adopt an ordinance to establish a local short-term residential rental registry. In 2018, Alexandria established its short-term rental registry which is maintained by the Department of Finance. At the time of the registry adoption, the City Council determined that regulation of short-term rentals should be handled via existing City Code and Zoning Ordinance regulations.

Due to recent calls for additional regulation of short-term rentals, the City Council directed staff to research the topic, provide a report and presentation, and begin a study to include community engagement. Below are the report and presentation shared with City Council this spring:

• Alexandria Short-Term Rental Data and Proposed Study Memorandum to City Council (May 2, 2024)
• Presentation to City Council (May 28, 2024)

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Below is the anticipated timeline for the continued study and opportunities for community input. This schedule may be extended if initial engagement suggests additional time will help resolve the issues identified. Information will be updated as it becomes available.

• May/June: Continue research on short-term rental regulations implemented in other jurisdictions.
• Share information with community and gather initial feedback.
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• Planning Commission workshop on proposed text amendment language
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• November (dates TBD): Planning Commission and City Council public hearings on recommendations and proposed text amendment.

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POC viral load testing in an antenatal clinic setting for Ugandan pregnant women living with HIV: a qualitative implementation process analysis

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• Published: 26 June 2024
• Volume 3 , article number  44 , ( 2024 )

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• Norma C. Ware   ORCID: orcid.org/0000-0002-5039-9991 1 , 2 ,
• Monique A. Wyatt 2 , 3 ,
• Agnes Nakyanzi 4 ,
• Faith Naddunga 4 ,
• Emily E. Pisarski 2 ,
• Juliet Kyomugisha 4 ,
• Juliet E. Birungi 4 ,
• Michelle A. Bulterys 5 ,
• Brenda Kamusiime 4 ,
• Alisaati Nalumansi 4 ,
• Vicent Kasiita 4 ,
• Andrew Mujugira 4 , 5 &
• Connie L. Celum 5 , 6  

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Introduction

Point of care viral load (POC VL) testing improves viral suppression and retention in HIV care, and is increasingly being integrated into routine health services for African pregnant women living with HIV. We examined processes of implementing POC VL testing in antenatal care and at delivery for Ugandan mothers living with HIV as part of a pilot randomized trial (Clinical Trial Number : NCT05092997).

We conducted individual qualitative interviews with 12 clinical and research staff who implemented POC VL testing and 22 mothers who received POC VL testing using the Xpert® HIV-1 Viral Load Assay (Cepheid Inc., Sunnyvale, CA, USA). An inductive, content analytic approach was used to examine the interview transcripts. The analysis addressed the question: How did a group of Ugandan health care providers approach the process of implementing POC VL testing in antenatal care and at delivery for mothers living with HIV?

The analysis yielded three themes. (1) Staff created an efficient system of communication and then relied on that system to coordinate testing procedures. (2) They also found ways of increasing the speed and efficiency of the testing process. (3) They adopted a “mother-centered” approach to implementation, prioritizing the needs, preferences, and well-being of women in planning and carrying out testing procedures.

As POC VL testing becomes more widely used across high HIV burden settings, understanding how implementers approach the implementation process and what they do to make an intervention successful will be an important part of evaluating feasibility.

Clinical Trial Number: NCT05092997.

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1 Introduction

Viral suppression during pregnancy and postpartum sustains the health of mothers living with HIV and reduces risk of HIV transmission to newborns [ 1 , 2 ]. Viral suppression requires adherence to antiretroviral therapy (ART), yet suboptimal adherence and disengagement from HIV care are common among pregnant women, especially after giving birth [ 3 , 4 , 5 , 6 ].

Point of care viral load (POC VL) testing reduces turnaround time from sample collection to availability of results [ 7 , 8 , 9 , 10 ], and increases rates of viral suppression and retention in care [ 7 , 11 ]. Studies comparing results of POC with laboratory-based viral load testing in diverse African health care settings confirm POC VL test results are accurate and reliable [ 10 , 12 , 13 ].

Uganda adopted viral load testing as the preferred means of monitoring response to HIV treatment in 2015 [ 14 ]. Currently, mothers living with HIV and taking ART receive viral load testing at the initial antenatal care (ANC) visit and every three months thereafter throughout pregnancy and breastfeeding. Newly diagnosed mothers receive VL testing at the initial ANC visit if CD4 test results reveal CD4 to be < 200 cells/mm 3 . For virally suppressed mothers, the test is then repeated every three months throughout pregnancy and until cessation of breastfeeding [ 15 ].

Presently, blood samples collected for VL testing at local clinics in Uganda are routed through a network of “hub” facilities to central health laboratories for processing, and the results returned to clinics via the same network [ 16 ]. Once test results have arrived at the clinic, they are typically reported to patients at the next follow-up visit. The entire process can take weeks or months, delaying needed clinical action.

A few studies have evaluated the impact of POC VL testing on viral suppression rates for pregnant and postpartum women in Africa, with mixed results. Delivery of POC VL testing with enhanced viral load counseling and phone follow-up by peer mothers substantially increased rates of viral suppression for pregnant and postpartum women in a recent study taking place in rural southwest Uganda [ 17 ]. Other evaluations report no statistically significant effect [ 9 , 18 ].

POC viral load testing is increasingly being integrated into routine antenatal care and as part of delivery for African pregnant women living with HIV [ 13 , 19 ]. To inform this process, we offer results from an analysis of qualitative data addressing the question : How did a group of Ugandan health care providers (“implementers”) approach the process of implementing POC VL testing in antenatal care and at delivery for mothers living with HIV ? The analysis was part of an intervention development study of POC VL testing and HIV treatment outcomes for pregnant and postpartum women taking place in Kampala, Uganda (The Kingasa Study).

2.1 Study design

The Kingasa Study (“It benefits me”, in Luganda, the local language) was a multi-method pilot randomized trial using a factorial design, in which 151 Ugandan pregnant women living with HIV who were at least 18 years of age, had partners of unknown HIV status, and were receiving antenatal care were randomized to an intervention intended to improve HIV treatment outcomes or standard of care (SOC). The intervention consisted of POC HIV-1 viral load testing with same day adherence counseling for participating women, and an invitation to visit the clinic for HIV testing and other preventive screenings for their male partners. SOC consisted of laboratory-based viral load testing for women with reporting of results at the next clinic visit, following Ugandan National Guidelines [ 15 ] (Clinicaltrials.gov: NCT05092997).

Questionnaire data were collected from women every three months until three months postpartum. Sociodemographic information was collected at baseline; information on birth outcomes and self-reported ART adherence were collected at follow-up. The primary outcome of the trial was viral suppression at three months postpartum. Trial results are reported elsewhere [ 20 ].

2.2 Setting

The Kingasa Study took place at a Level III public health clinic in Kampala, Uganda. More than 26,000 ANC visits took place at the clinic in 2022–2023 [ 21 ]. The clinic also offers general outpatient services and HIV testing and treatment. POC HIV-1 VL testing for mothers participating in Kingasa took place at enrollment, delivery, and at three months postpartum. Blood draws for testing were carried out principally by laboratory technicians, but also by nurses and midwives. Sample collection took place in consulting rooms, in or near the clinic’s maternity ward, and at offsite locations (participants’ homes, other clinical facilities). Samples were processed using the Xpert® HIV-1 Viral Load Assay (Cepheid Inc., Sunnyvale, CA, USA) located in the clinic laboratory. The Xpert Assay processes up to four blood samples simultaneously, producing results approximately 90 min after samples are loaded. Laboratory technicians processed the samples, and handed the results off to nurses, who reported them to patients.

2.3 Qualitative data collection

The Kingasa Study included a qualitative component in which data were collected from two groups: (1) clinical and research staff who implemented the intervention (“implementers”), and (2) a convenience sample of mothers who received POC HIV-1 VL testing using the Xpert Assay. Single in-depth qualitative interviews were carried out with all participants using semi-structured interview guides by authors BK, AN, and VK. Participants were contacted by telephone by interviewers to explain the research and the meaning of participation and set up an interview appointment. Implementer interviews covered aspects of personal and professional background, knowledge and perceptions of POC VL testing, and experiences of implementing POC VL testing in Kingasa. Mothers’ interviews covered aspects of personal background, quality of the partnered relationship, and attitudes, perceptions and experiences of POC VL testing. Interviews took place in mutually agreeable, private locations in the local language (Luganda) or in English. They were audio-recorded and transcribed in English as soon as possible after each interview was completed. Interviews lasted about an hour. Qualitative interviews were carried out beginning in December 2021 and ending in September 2022.

2.4 Qualitative data analysis

An inductive, content analytic approach was used to examine the interview transcripts for the analysis reported here [ 22 ]. We reviewed all the transcripts to identify and extract content relevant to process —what interviewees said about how the Kingasa intervention was implemented. Relevant content was grouped iteratively through repeated readings into conceptual clusters based on similarities. We then grouped clusters to form larger thematic concepts. Descriptive categories were developed to represent the concepts. To develop descriptive categories, we named, specified, and illustrated the concepts using excerpts from the data. For this analysis, data were not formally coded. The analysis yielded three categories reported as Results, below.

3.1 Characteristics of participants

3.1.1 implementer participants.

Twelve of 16 clinical and research staff who implemented the Kingasa intervention took part in interviews for the qualitative study. The remainder declined to participate. Six implementer interviewees were women; six were men. Three-quarters had university-level educations. Half (N = 6) were laboratory technicians; five were nurses and/or counselors; one was a midwife. Median age of implementer interviewees was 32 years (See Table  1 ).

3.1.2 Participating mothers

Twenty-two (15%) of mothers participating in the Kingasa Study took part in interviews for the qualitative component. Median age was 27.5 years. Half (50%, N = 11) had at least some secondary education; half (50%, N = 11) were working to earn income.

Mothers reported being with their current male partners for a median of three years (IQR: 1.75 to 6). Median total reported pregnancies was four (IQR: 3–5); median reported number of living children was three (IQR: 2–4). Median reported years since HIV diagnosis was four (IQR: 2–6.98). All mothers reported taking ART at the time of participation. Nearly two-thirds (64%, N = 14) reported having disclosed their HIV status to their current partner. Results of POC HIV-1 VL testing at enrollment revealed all but one of the mothers to be virally suppressed (95%, N = 21); at delivery all were virally suppressed (< 50 copies/ml) (See Table  2 ).

3.2 POC HIV-1 VL testing implementation

In qualitative interviews, half (50%, N = 11) of mothers reported receiving results of their POC HIV-1 VL testing at enrollment on the same day as sample collection. Half (50%, N = 11) of births took place at the study clinic. The remainder took place at other health facilities. Slightly fewer than half of blood draws for POC VL testing at delivery were completed at the study clinic (41%, N = 9); about a third (37%) were done at home. All blood draws described by mothers were reported to have taken place after, rather than before, the birth (See Table  3 ).

3.3 Qualitative results

Below we present the three thematic descriptive categories resulting from the inductive content analysis: 1. Coordination and Communication; 2. Speed and Efficiency; and 3. “Mother-centeredness”.

3.3.1 Coordination and communication

Implementers emphasized coordination and communication in their accounts of carrying out POC viral load testing. For example, they created a secure, instant messaging chat group, and used it to keep each other updated in real time.

When a mother presented at the clinic for delivery, midwives alerted colleagues via the chat group. Staff then met to assess the mother’s condition and decide on the best time and location to collect a blood sample for POC VL testing. They felt blood draws could be carried out in the maternity ward, the lab, or another nearby location offering privacy. For implementers, optimal moments for drawing blood at delivery were either early in labor or 30–60 min after the birth. The actual timing varied with the mother’s well-being, preferences, and circumstances.

About half (45%) of women in the qualitative sample delivered at a health facility outside the study clinic. This complicated sample collection for POC VL testing for implementers, as medical staff at the external sites had to give permission for a visitor to carry out a procedure involving a patient under their care. Multiple interactions and/or a letter of introduction were usually required to obtain permission. Rather than struggle with these coordination and communication challenges, implementers often chose to meet mothers in their homes for blood draws. This usually meant testing was completed a few days after delivery.

Blood draws at home also entailed extensive coordination and communication. Multiple phone calls were required to arrange appointments, get directions, and ensure all relevant parties were informed and kept up to date. The process usually began with a call from an implementer to the mother confirming permission for a home visit and fixing a time to meet. The caller explained that the blood draw would be done by a laboratory technician, whom the mother likely had not previously met. Following the conversation, the caller contacted laboratory staff to inform them a home visit was needed. The technician making the visit would then follow up with another call to the mother to introduce himself or herself, confirm agreement, and get directions. The technician would sometimes need to call again while en route for directions or to confirm the time was still convenient. One interviewee described the process this way:

“ …the mother [must be] informed that someone is coming to take off samples… You cannot just come out to meet her and be like, ‘I have been told to take off samples from you.’ She must have gotten the information prior and she is expecting you. [At the same] time we must keep in touch with those people that sent us to the field. Even when I reach the mother, before taking off samples I call and tell a research staff that I have arrived…” Laboratory Technician

Home visits to mothers who had not disclosed to partners could be particularly challenging. Careful planning and coordination were required to avoid encountering partners during the visit. If this proved impossible, the visitor had to find a way of explaining why s/he was there and carry out the procedure, while at the same time avoiding unwanted disclosure. One home visitor recounted this experience:

“When I got there, they welcomed me. The husband gave me a seat and we started conversing. The man had a lot of questions. I told him, ‘when these mothers come to us at the facility we always encourage them to come with you [partner] … but you did not come. So, allow me to explain to you why we are following [your wife]’. But I did not disclose to him that she is HIV positive. … I told him that we followed her home because she did not deliver from [study clinic] … and she was discharged without us knowing what packages were given to her and how she was faring. So that is why I am here….” Laboratory Technician

Implementer coordination and communication were facilitated by access to mobile phone technology.

3.3.2 Speed and efficiency

POC VL testing was known as “the quick, 90-min test” at the study clinic. Implementers introduced the test to mothers as taking 90 min from blood draw to receipt of results. In fact, 90 min was the time required for the Xpert Assay to process a sample once it had been loaded into the system. The time needed to collect the sample, transport it to the lab, complete preliminary procedures, and hand the results off for reporting to a waiting mother lengthened total testing time. Implementers recommended lengthening estimates of the time required from blood draw to receipt of results, when introducing POC VL testing to mothers:

“I would not tell [mothers] that [POC VL testing] takes 90 minutes because it exceeds that... I think it should be like two hours. There should be an allowance for things that happen in between.” Nurse

Implementers accepted the expectation that POC VL test results would be available in 90 min as part of the Kingasa intervention. To meet this expectation, they set a brisk pace for activities associated with testing. Implementers developed a number of strategies to increase the speed and efficiency with which samples could be collected, analyzed, and the results returned to mothers. They used the instant messaging group chat to keep in touch so potential gaps between steps in the process could be minimized, and built redundancy into the distribution of skills, roles, and functions needed to complete the testing process. This saved time by enabling staff to fill in for each other to complete required tasks. One implementer described it this way:

“[What] we did was to empower our midwives and nurses. We had a session and taught them how to collect the samples properly. … It was something they took on, and at some point, they were collecting the samples and we would just do checks on them to see that they were properly collected.” Laboratory Technician

Often implementers had to stretch themselves to keep up the pace. To shorten turnaround time, for example, technicians might return to the laboratory when they were off duty, in order to process samples and produce results as quickly as possible. Technicians also worked after hours to finish processing samples in a single day. One technician described the following experience:

“ I went to [off-site location] to collect the sample. I remember I left [the clinic] at 2:00 pm and by 2:30 pm I was there. I left by 6:00 pm and I had to come back and run the samples that very evening because we are supposed to run them there and then. I left [the lab] around 8:00 pm to go back home.” Laboratory Technician

Despite efforts to maximize efficiency, mothers sometimes waited several hours at the clinic to receive their POC VL testing results. Implementers took steps to make the waiting time easier by providing snacks and/or a quiet space to rest. Sometimes, mothers could not wait long enough to receive their results in person. In these cases, they returned to clinic at a later date, or arranged with staff to receive their results over the phone. One mother explained her experience:

“…study staff drew a blood sample … and that sample was taken down [to the laboratory] for testing. That same study staff came back and said that there was no electricity and I was told that I am going to wait longer. While I was waiting, it started raining and I told them that I have to go before it is heavy rain. Study staff told me that it is okay, they will contact me on phone and tell me my results. One hour after I had reached home, I was called and study staff told me that the results have showed that my blood is good…”. Mother

3.3.3 “Mother-centeredness”

Implementers’ descriptions of their experiences in carrying out POC VL testing suggest they placed mothers at the center of the intervention, letting their needs and preferences drive the implementation process wherever possible. We have seen this in how they carried out home visits for blood draws, when visiting laboratory technicians checked in repeatedly with mothers en route, and avoided approaching a residence until receiving explicit permission to do so. We see it also in the emphasis they placed on offering choices to mothers. The choice between receiving POC VL testing results in person on the same day, in person on a subsequent day, or over the phone is one example of this:

“You agree with the mother on how she wants to receive the results. … We can always give clients options that are flexible, because you are not going to make the mother sit there and wait for results when she has a baby at home and has not had lunch. … Some mothers come to the facility, so they can walk in. A mother can also give you her phone number if she has one. You ask what time she wants to be called and you record it and call her…” Nurse

Kingasa implementers’ “mother-centered” approach is also evident in the investments they made in providing support and promoting mothers’ well-being. An example is the practice of contacting mothers by phone between clinic appointments to check on their pregnancy and HIV-related needs. Mothers felt cared for as a result. Said one mother after receiving home delivery of an ART refill:

“I really got support from Kingasa Study because there was even a time I was sick and the study staff brought me medicine (ART) at home. I simply called them and they had no problem bringing me ART at home. The calls they made asking me how I am after I gave birth also showed that they were caring for me.” Mother

While adhering to the intervention protocol, implementers eschewed a “one-size-fits-all” approach to implementation, opting instead to individually assess situations and tailor intervention activities accordingly. The care taken to understand each mother’s situation when choosing a moment for blood draw at delivery testifies to this. One implementer characterized Kingasa’s individualized, “in-the-moment” approach to caring for mothers this way:

“...we should not get used to thinking people are the same. [We should] treat everyone the way they are, … the way they have come, and not ever think that someone’s experience is the same as someone else’s…Every client is unique and they all go through different things. If you think what you dealt with yesterday is what you will deal with today that is when we lose it. … Let us give them a kind of holistic environment and treat them as they come, not as they were yesterday.” Nurse

4 Discussion

Our inductive content analysis of implementers’ and mothers’ qualitative accounts yielded three themes that speak to how health care staff worked to implement the Kingasa POC HIV-1 VL testing intervention. They created an efficient system of communication and then relied on that system to coordinate POC VL testing procedures. They looked for and found ways of increasing the speed and efficiency of the testing process. And they prioritized the needs, preferences, and well-being of participating mothers in planning and carrying out testing procedures and reporting results.

This qualitative evaluation privileges the voices of implementers. Implementer voices have been represented in a few other studies focusing on POC VL testing, usually to report perceived benefits and challenges, and/or suggestions for how testing can be improved [ 23 , 24 , 25 ]. In this study, we asked implementers to describe how they carried out testing activities. As a result, we learned what implementation was like for them – how they approached it, its impact on established ways of working, and adjustments they made to ensure testing procedures were completed successfully.

To date, most studies examining the feasibility of POC VL testing in African health care settings have focused on implementation outcomes, e.g., number of tests completed daily, accuracy of test results, and/or turnaround time to receipt of results [ 10 , 12 , 13 , 19 ]. In contrast, our study was process-oriented. Our process orientation offers a complementary perspective from which to evaluate feasibility, asking questions about how implementers organized to make POC VL testing happen. Both outcome and process-oriented evaluations are essential to an accurate and thorough understanding of feasibility.

In implementation science, adaptation has been defined as “a process of thoughtful and deliberate alteration to the design or delivery of an intervention, with the goal of improving its fit or effectiveness in a given context” [ 26 ]. A significant adaptation made to the Kingasa POC VL testing intervention in the process of implementation was the use of home visits to draw blood for testing at delivery for mothers who gave birth outside the study clinic.

The Enhanced Framework for Reporting Adaptations and Modifications (FRAME) specifies a set of parameters for the characterization of adaptations, in the interests of promoting understanding of the kinds of adaptations that take place, and how and when they occur [ 26 ]. Applying FRAME parameters, we may characterize the home visit adaptation in Kingasa as an unplanned modification to delivery of POC VL testing. The adaptation was “unplanned” in the sense that it represented a solution to an unanticipated problem that came up during the implementation process, i.e., the difficulty of collecting blood samples while mothers were inpatients at another clinical facility. Potential risks to confidentiality and the possibility of non-voluntary disclosure of HIV status as part of the home visit adaptation were recognized by implementing staff, who worked to minimize these risks in ways described here while trying to ensure the benefits of POC viral load testing were made available. The home visit adaptation was intended to facilitate continued delivery of the Kingasa intervention’s core component of POC VL testing, making it “fidelity consistent,” in FRAME terms.

Home visits for blood draws were a way of maximizing the number of Kingasa mothers who would receive and benefit from POC VL testing at delivery. At the same time, the effort appears to have been resource-intensive, requiring relatively large investments of time and money to implement. Whether home visits for sample collection enhance or detract from the feasibility of POC VL testing for pregnant women at delivery is a question that merits future study.

Several suggestions for optimizing implementation of POC VL testing for pregnant women emerged from our analysis. One suggestion from implementers was to introduce POC VL testing in a way that sets realistic expectations for turnaround time. Including time required to complete the entire testing process in descriptions to recipients will reduce pressure on implementers and frustration for individuals awaiting their results. A second suggestion was to build in overlap in implementer roles and functions when planning the implementation process. In Kingasa, for example, implementers described how training midwives alongside laboratory technicians to perform blood draws accelerated sample collection. Ensuring a reliable communication system is in place was a third suggestion for optimizing implementation of POC VL testing for pregnant women living with HIV.

This study contributes to research on intervention implementation process by detailing how one group of health care professionals made POC VL testing happen for Ugandan pregnant women living with HIV and receiving antenatal care in a Level III public health clinic. We recognize the study’s limitations. Women qualitative participants comprised a convenience sample; however, this analysis prioritized understanding the experiences of implementers. Because Kingasa was a research study, we do not claim the approach Kingasa staff took matches the approach implementers might take outside a controlled research context. Finally, we acknowledge that implementer accounts of their activities in interviews may not correspond completely to “what really happened.” Data from direct observations of POC VL testing implementation in addition to individual interviews would have allowed for triangulation of two data sources. The additional perspective on implementation process provided by two data sources would have strengthened the validity of analytic results.

5 Conclusion

As POC VL testing becomes more widely used across high HIV burden settings, understanding how implementers think about and approach the implementation process and what they do to make an intervention successful will be an important part of evaluating feasibility.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Code availability

Not applicable.

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Acknowledgements

The authors gratefully acknowledge the Kingasa Study Team, who implemented the POC VL testing intervention, and the qualitative study participants, who took part in interviews. We also appreciate the contributions of the study clinic facility team, who were instrumental in implementing the Kingasa Study. We recognize the contributions of Paul Sendiwala, Grace K. Nalukwago, Collins C. Twesigye, and Jade Boyer. Finally, we thank Gwynn Stevens and Dipti Lallubhai for facilitating the donation of the Xpert instrument and Xpert HIV-1 Viral Load test kits.

This work was supported by a research grant to Dr. Celum from the US National Institutes of Mental Health [NIMH R01 MH113434].

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Norma C. Ware

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Norma C. Ware, Monique A. Wyatt & Emily E. Pisarski

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Monique A. Wyatt

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Agnes Nakyanzi, Faith Naddunga, Juliet Kyomugisha, Juliet E. Birungi, Brenda Kamusiime, Alisaati Nalumansi, Vicent Kasiita & Andrew Mujugira

Department of Global Health, University of Washington, Seattle, WA, USA

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Contributions

NCW and MAW designed the qualitative study. BK, AN(alumansi), and VK collected the qualitative data. EEP coordinated the data collection process and contributed to data analysis. CC conceptualized and designed the Kingasa Study. AN(akyanzi), FN, AM and CC implemented the Kingasa Study. NCW and MAW analyzed the qualitative data. NCW drafted the manuscript. All authors reviewed and approved the final manuscript.

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Correspondence to Norma C. Ware .

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Ethics approval and consent to participate.

The Kingasa Study was approved by the University of Washington Human Subjects Review Committee (STUDY00009286), the Mildmay Uganda Research Ethics Committee (MUREC 0707-2020), and the Uganda National Council for Science and Technology (HS991ES). All participants provided written informed consent to be interviewed as part of the overall study consent process.

Competing interests

Cepheid, Inc. donated the GeneXpert system and viral load test kits used in the Kingasa Study. AM reports a grant from Gilead Sciences, Inc., outside this work, and has served as advisor to ViiV Healthcare. CC has served as scientific advisor to Gilead Sciences and Merck.

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Ware, N.C., Wyatt, M.A., Nakyanzi, A. et al. POC viral load testing in an antenatal clinic setting for Ugandan pregnant women living with HIV: a qualitative implementation process analysis. Discov Health Systems 3 , 44 (2024). https://doi.org/10.1007/s44250-024-00103-8

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Money blog: HSBC, Nationwide and Virgin Money hit by glitches; how to stop your car being stolen - or even 'cannibalised'

Welcome to the Money blog, your place for personal finance and consumer news and advice. Let us know your thoughts on any of the topics we're covering using the comments box below.

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By Emily Mee, news reporter

A car was stolen roughly every eight minutes in the UK last year, according to DVLA figures. 

Some 64,087 vehicles were reported stolen - an increase of 5% on the previous year. 

While car thefts are on the rise, reports have also highlighted a growing trend of "car cannibalism" - when criminals rip parts off cars to order. 

Bonnets, bumpers and headlights are among the parts often nicked by thieves. 

It might sound like a familiar refrain at this point, but consumer rights expert Scott Dixon says the cost of living crisis is largely to blame. 

Scott, who runs The Complaints Resolver , told us the costs of spare parts and insurance have "rocketed" post-COVID - driving opportunists to turn to crime. 

He also pointed to a scarcity of decent second-hand cars on the market currently, saying people are "holding onto their cars for longer because they can't afford to change them". 

How can you protect your car? 

Scott says there are numerous ways you can prevent your car from becoming a target - and many of them are cheap and simple. 

Get your keys recoded

If you're buying second hand, getting your keys recoded can give you additional security. 

Scott says it's possible the person you bought from could have copies of the keys, allowing them to steal your car or break in. 

Fit a tracking device

This should be fitted professionally, and while it won't stop your vehicle from being stolen, it will increase the chances of police being able to track it down and return it. 

You should be aware, though, that you'll need to pay a fairly costly annual subscription fee. 

Secure your number plate

Some thieves will take number plates so they can steal petrol from forecourts - and Scott says some are now doing this to escape ULEZ fines. 

He recommends getting anti-theft screws to secure your number plate. 

Keep your car tidy

Handbags, phone leads, sat-nav holders and paperwork can all attract the attention of opportunist car thieves. 

Scott says many people are "too careless and complacent" with this - and it's completely free to fix. 

Fit a steering or handbrake lock

You can get these on Amazon for less than £20 each - and because they're visible, they can also act as a deterrent. 

A pedal box, which encases the pedals in a highly visible metal box, is another option. 

A good wheel clamp - Scott recommends this one  - can be bought on Amazon for about £30. 

Another visible deterrent is a sticker to say the vehicle is alarmed or has a tracker fitted. 

Think about where you park

Thieves are more likely to target quiet and dimly lit areas, as well as quiet side streets, Scott says. 

If you can, try to park in a well-lit and busy area - preferably with CCTV. 

Install cameras 

You could keep your dashcam recording through the night (which could capture anyone walking in front of the car) and put up signs stating you have cameras around. 

Fit a car alarm or immobiliser

Although most modern cars have these fitted, older cars often don't. 

Plus, having a professionally fitted alarm or immobiliser could lower your insurance premium. 

Etch your car windows 

You can buy a car window etching kit for less than £15, including warning stickers to show the identification number is traceable. 

If you have your Vehicle Identification Number (VIN) etched onto the doorframe, windows and steering wheel, it can deter thieves from stealing the vehicle or its parts as it will be harder to sell stolen parts if they're personalised. 

Window tinting

Of course, you'll only be able to do this to a certain extent as the law states the front windscreen has to let in at least 75% of light through. For front side windows, you need 70%. 

But there are no rules around the rear windscreen or rear passenger windows, and having a tint can deter criminals from looking into the car. 

Take steps to prevent relay theft

An increasingly popular way to steal cars is through relay theft - when criminals use devices to relay signals from the car key to the car. 

One person will get near enough to the key inside the house to pick up the signal, while a second person will hold another device next to the vehicle. 

All keyless cars are vulnerable to relay theft - but in particular, Audi, BMW, Ford, Hyundai, Land Rover, Mercedes and Volkswagen cars are the most popular targets.

You can help prevent it by keeping your keys in a "Faraday pouch" - which has a lining preventing the keys inside from receiving or transmitting radio frequency signals.

A pack of two is available online for roughly £8. 

Another option is to use a metal container, as the relay device cannot pass through metal. 

You should also avoid storing your keys near doors or windows. 

Shoppers have been buying bigger TVs to enjoy this summer's European Championships, according to the electrical retailer Currys.

The chain said UK sales were up by more than 30% in the past month, with "supersize" screens — 85-inch and above — selling well in the run-up to the Euros.

"Having a third of the TV market and the Euros being a big event for many people, we're seeing that super-sizing trend keep on giving," said Currys chief executive Alex Baldock.

The most popular, and also cheapest, 85-inch TV on the Currys website costs £999. 

The most expensive super-size TV is a 98-inch offering from Samsung that will set you back £9,499.

Currys reported adjusted pre-tax profits of £118m for the year to 27 April. That represented a 10% increase from the previous year's profits of £107m.

Like-for-like sales for Currys UK and Ireland declined by 2% to £4.97bn in the 12 months to 27 April, with consumer confidence knocked by high inflation levels and rising interest rates.

"We can see our progress in ever-more engaged colleagues, more satisfied customers and better financial performance," Mr Baldock added.

Selling your home can be expensive, with the range of fees that come as part of the selling process meaning costs can really rack up.

Those costs are usually present whether you visit a bricks and mortar estate agents on the high street or if you go online, although Purplebricks has marketed itself as an exception to the rule.

Since December, it has launched a new pricing structure that enables sellers to list their homes without paying a penny, making it the only completely free online estate agent in the UK.

Purplebricks previously charged a fixed fee of £1,349 (including VAT) to sell your house, with that figure rising to £2,999 for those based in and around London. 

That needed to be paid upfront or not later than 10 months after the property was first advertised, even if it went unsold.

Now, after being bought out by rival online estate agency Strike last year, Purplebricks is offering a free service, no strings attached.

Is there a catch, though?

There's no such thing as a free lunch or, it seems, a totally free way to sell your house.

If you'd like to pay more to unlock extras and upgrades, you can do so, with a 'Boost' and 'Full House' package costing £899 and £1,499 respectively.

All estate agents are also required by law to carry out anti-money laundering checks on everyone selling a property.

Typically, that cost is incorporated by estate agents into their service fees. However, as Purplebricks' service is free, it has implemented a separate £60 Anti-Money Laundering (AML) fee for sellers.

What's more, there's also no Rightmove listing included as part of its free service.

As the UK's biggest property portal market, attracting more buyers and sellers than anyone else, Rightmove can help sell your home much faster. 

Purplebricks does include a free Zoopla listing, but adding Rightmove is an optional add-on that will set you back £299.

So, how does Purplebricks make money?

Add-ons and extras. 

Purplebricks will be hoping to make money by customers opting for optional extras or premium services.

As well as the Rightmove example mentioned above, professional photographs and a floorplan will cost £699, while hosted viewings of your property will come at a charge of £899.

Purplebricks can also work with sellers and buyers to help them find the right mortgage deal and by offering them conveyancing services. 

It's important to remember that there is no obligation to buy any of the add-on services, though some will undoubtedly come in handy.

Purplebricks is clear about its up-selling tactics too. This is what its website says:

We’re fully transparent about what little extras we offer and where your money is going – so it really is your choice. When our agent speaks to you, they’ll talk you through the options, and then you can decide if it’s right for you.

In the last few minutes, HSBC has confirmed issues earlier today - with online, mobile banking and payments - have been resolved.

 More now on the news that a string of banks have been suffering from glitches that have delayed payments being made for millions of customers.

Nationwide, Virgin Money, HSBC and Barclays all reported issues with their digital banking services this morning.

It comes on a day many workers are due to receive their wages and many households are paying their bills.

Here are the latest updates from each bank affected:

Virgin Money has announced its mobile banking app is now "fully restored" as of 12.52pm.

"Like other banks, we’re working hard to process the backlog of payments delayed as quickly as possible, and will update you as soon as we can," it posted on X.

"If you have tried to send a payment from your Virgin Money account and received an error message, but it has debited your Virgin Money account, please do not try to make the payment again, as it is in the queue and will be processed."

HSBC customers can also now log on to personal banking both online and on mobile. 

The bank says there are still "secondary issues" they are trying to fix, including viewing recent transactions.

"Customers sending payments may see a slow response or see a failure notice," it added. 

"Please check with the recipient or view your recent transactions in the mobile app via the notifications bell icon in the top right corner before attempting to send the payment again."

Nationwide has reported no issues with its banking app.

In response to the problems receiving salary or pension payments, the building society says payments are being processed and expects them to be paid into accounts today.

Barclays says that some of its customers are reporting that incoming payment issues have now been fixed.

Replying to one customer on X, the bank said: "We have been experiencing some issues with the Faster Payment Scheme that most banks operate through when making payments, however we have had some positive news in the last 5 minutes confirming that the issue is now resolved! 

"With that being said, any payments that you have tried to make should now go through for you so please keep an eye out on your account for these to be reflected. If you do need any further help then we are here 24/7 for you."

On Barclays' service status page, all indicators have now been turned green to show there are no ongoing issues.

Another bank has been affected by technical issues with payments today.

In a reply to a customer on X, Barclays said the glitch was "happening across all banks".

The Barclays reply said: "So sorry to hear you've been caught up in the issue with regards to the payments being made and received. This is an issue with the faster payment system and it's happening across all banks."

More now on the IT issues affecting people who bank with Nationwide, HSBC and Virgin Money.

Customers of all three have been hit with problems affecting their banking services today.

On what is pay day for many across the country, some customers have been unable to receive their salaries or pension payments.

According to the website DownDetector, more than 7,000 problems were reported at about 8.45am this morning.

The site also shows a spike in reports of outages for high street bank Virgin Money and building society Nationwide.

Customers of the banks are particularly upset by the timing of the glitches, with many people needing to pay their bills.

"I'm waiting on money coming into my bank which is still not received even though it's been sent. I can't pay any bills. Even though I have the money for bills," said one customer on X.

"My bills are bouncing and I can’t pay for a train ticket I need in the next hour," said another.

Bank responses

Nationwide  customers complained on X they had not received their wages into their accounts.

The building society said it is "aware there is a delay with some customers receiving their salary or pension payments today".

"These payments are being processed, and will be paid into your account today," it added. "Sorry for any inconvenience this is causing."

Virgin Money  addressed its issues on X this morning, warning customers not to attempt to process payments a second time if they had already tried once,

The bank issued an update on X later, adding - as of 11.08am - it is "aware of intermittent issues with accessing online banking and our app, which we're working to resolve as quickly as possible".

HSBC apologised to its customers and said its IT teams were working on the issue.

In a second update at 12.22pm, the bank said customers could now log into personal online and mobile banking but could still not view recent transactions.

Earlier, we brought you the news that HSBC customers have reported IT issues with mobile banking and the bank's app (see 9.37am post).

Now Nationwide has also said there was a "delay with some customers receiving their salary or pension payments today".

Read more in our breaking news story...

Forget the bank of mum and dad, the bank of gran and grandad is coming into play as parents struggle to afford school trips.

Some 23% of parents say they have had to make cutbacks - even to essentials - to fund them, while 10% said grandparents had paid for the trip and 8% said an aunt or uncle had chipped in.

The research, undertaken by public sector insurer Zurich Municipal, found one in five financially pinched parents felt embarrassed about struggling to pay for trips.

"School trips bring a plethora of benefits to young lives, it's heartbreaking to see so many could miss out due to cost," said Tilden Watson, head of education at Zurich Municipal.

"These trips can also expose some children to new places and experiences that they wouldn't necessarily get to enjoy with their families so they really do offer a window to the world they otherwise wouldn't see."

OnePoll surveyed 1,000 parents of children aged five to 16 across the UK in May.

More than a third (35%) of parents believed school trips are critical to their child's education.

A major bank has apologised to its customers for IT issues.

In a post on X just before 9.30am, HSBC said: "We’re really sorry that some customers are having issues accessing personal online and mobile banking. 

"Our IT teams are working hard to get these services back to normal. 

"You can still authorise online card purchases via SMS."

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• university of new orleans
• campus news
• professor earns $345,000 grant to monitor vegetation in coastal louisiana

CAMPUS NEWS: JUNE 27, 2024

Coastal grant, professor earns $345,000 grant to monitor vegetation in coastal louisiana.

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Professor Maddie Foster-Martinez’s research will focus on determining vegetation establishment in coastal Louisiana areas.

University of New Orleans professor Maddie Foster-Martinez is the recipient of a two-year $345,000 grant from the RESTORE Act Center of Excellence - The Water Institute . Through funding from fines and penalties in the wake of the 2010 Deepwater Horizon oil spill, these grants fund research that directly supports planning and implementation of Louisiana’s Coastal Master Plan. Foster-Martinez’s research will focus on determining vegetation establishment with custom-built sensors.

Foster-Martinez is an assistant professor in the Department of Earth and Environmental Science and Department of Civil and Environmental Engineering, and is a member of the Pontchartrain Institute for Environmental Sciences at the University of New Orleans. Her research focuses on coastal wetlands and leveraging vegetation for climate change mitigation and adaptation.

Two of the main strategies to reverse land loss in coastal Louisiana are river diversions and pumping sediment to create marshes in shallow water, according to Foster-Martinez. For both strategies, the presence of marsh plants is critical in how much land is built and how long it lasts, she said.

“For both types, we don't know exactly what conditions make it possible for marsh plants to first start growing, but if we could figure that out, then our models to predict land building over time could be much more accurate,” Foster-Martinez said. “And we could do a better job of creating the right conditions for marsh plants to first establish.”

Foster-Martinez and her research team will make detailed measurements at three sites across Louisiana, two in natural deltas and one in a marsh creation. They will use customized sensors at each location to determine how much vegetation is being established.

“We know that a big increase in water level is occurring globally and will amplify within our lifetimes, in addition to more hurricane activity,” Foster-Martinez said. “It's important to understand how our coastal marshes function, so we can make informed decisions with accurate modeling. Our current models are quite good, but we can always do better. This project pushes us in that direction.”

The Water Institute was selected by the Louisiana Coastal Protection and Restoration Authority (CPRA) to serve as the state’s Center of Excellence. In this role, the institute administers a competitive grants program, in collaboration with CPRA, to support research that can help answer questions and provide guidance in the state’s $50 billion, 50-year Coastal Master Plan.

To select the projects, the Center of Excellence coordinated an external peer-review process where three independent subject matter experts, including Center of Excellence External Review Board members, evaluated each proposal. Representatives from CPRA also evaluated the proposals to help determine how well each proposal applied to advancing the Coastal Master Plan work.

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