typically a research project revolves around following three questions

Research Question 101 📖

Everything you need to know to write a high-quality research question

By: Derek Jansen (MBA) | Reviewed By: Dr. Eunice Rautenbach | October 2023

If you’ve landed on this page, you’re probably asking yourself, “ What is a research question? ”. Well, you’ve come to the right place. In this post, we’ll explain what a research question is , how it’s differen t from a research aim, and how to craft a high-quality research question that sets you up for success.

Research Question 101

What is a research question.

• Research questions vs research aims
• The 4 types of research questions
• How to write a research question
• Frequently asked questions
• Examples of research questions

As the name suggests, the research question is the core question (or set of questions) that your study will (attempt to) answer .

In many ways, a research question is akin to a target in archery . Without a clear target, you won’t know where to concentrate your efforts and focus. Essentially, your research question acts as the guiding light throughout your project and informs every choice you make along the way.

Let’s look at some examples:

What impact does social media usage have on the mental health of teenagers in New York?

How does the introduction of a minimum wage affect employment levels in small businesses in outer London?

How does the portrayal of women in 19th-century American literature reflect the societal attitudes of the time?

What are the long-term effects of intermittent fasting on heart health in adults?

As you can see in these examples, research questions are clear, specific questions that can be feasibly answered within a study. These are important attributes and we’ll discuss each of them in more detail a little later . If you’d like to see more examples of research questions, you can find our RQ mega-list here .

Research Questions vs Research Aims

At this point, you might be asking yourself, “ How is a research question different from a research aim? ”. Within any given study, the research aim and research question (or questions) are tightly intertwined , but they are separate things . Let’s unpack that a little.

A research aim is typically broader in nature and outlines what you hope to achieve with your research. It doesn’t ask a specific question but rather gives a summary of what you intend to explore.

The research question, on the other hand, is much more focused . It’s the specific query you’re setting out to answer. It narrows down the research aim into a detailed, researchable question that will guide your study’s methods and analysis.

Let’s look at an example:

Research Aim: To explore the effects of climate change on marine life in Southern Africa.

Research Question: How does ocean acidification caused by climate change affect the reproduction rates of coral reefs?

As you can see, the research aim gives you a general focus , while the research question details exactly what you want to find out.

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Types of research questions

Now that we’ve defined what a research question is, let’s look at the different types of research questions that you might come across. Broadly speaking, there are (at least) four different types of research questions – descriptive , comparative , relational , and explanatory . 

Descriptive questions ask what is happening. In other words, they seek to describe a phenomena or situation . An example of a descriptive research question could be something like “What types of exercise do high-performing UK executives engage in?”. This would likely be a bit too basic to form an interesting study, but as you can see, the research question is just focused on the what – in other words, it just describes the situation.

Comparative research questions , on the other hand, look to understand the way in which two or more things differ , or how they’re similar. An example of a comparative research question might be something like “How do exercise preferences vary between middle-aged men across three American cities?”. As you can see, this question seeks to compare the differences (or similarities) in behaviour between different groups.

Next up, we’ve got exploratory research questions , which ask why or how is something happening. While the other types of questions we looked at focused on the what, exploratory research questions are interested in the why and how . As an example, an exploratory research question might ask something like “Why have bee populations declined in Germany over the last 5 years?”. As you can, this question is aimed squarely at the why, rather than the what.

Last but not least, we have relational research questions . As the name suggests, these types of research questions seek to explore the relationships between variables . Here, an example could be something like “What is the relationship between X and Y” or “Does A have an impact on B”. As you can see, these types of research questions are interested in understanding how constructs or variables are connected , and perhaps, whether one thing causes another.

Of course, depending on how fine-grained you want to get, you can argue that there are many more types of research questions , but these four categories give you a broad idea of the different flavours that exist out there. It’s also worth pointing out that a research question doesn’t need to fit perfectly into one category – in many cases, a research question might overlap into more than just one category and that’s okay.

The key takeaway here is that research questions can take many different forms , and it’s useful to understand the nature of your research question so that you can align your research methodology accordingly.

How To Write A Research Question

As we alluded earlier, a well-crafted research question needs to possess very specific attributes, including focus , clarity and feasibility . But that’s not all – a rock-solid research question also needs to be rooted and aligned . Let’s look at each of these.

A strong research question typically has a single focus. So, don’t try to cram multiple questions into one research question; rather split them up into separate questions (or even subquestions), each with their own specific focus. As a rule of thumb, narrow beats broad when it comes to research questions.

Clear and specific

A good research question is clear and specific, not vague and broad. State clearly exactly what you want to find out so that any reader can quickly understand what you’re looking to achieve with your study. Along the same vein, try to avoid using bulky language and jargon – aim for clarity.

Unfortunately, even a super tantalising and thought-provoking research question has little value if you cannot feasibly answer it. So, think about the methodological implications of your research question while you’re crafting it. Most importantly, make sure that you know exactly what data you’ll need (primary or secondary) and how you’ll analyse that data.

A good research question (and a research topic, more broadly) should be rooted in a clear research gap and research problem . Without a well-defined research gap, you risk wasting your effort pursuing a question that’s already been adequately answered (and agreed upon) by the research community. A well-argued research gap lays at the heart of a valuable study, so make sure you have your gap clearly articulated and that your research question directly links to it.

As we mentioned earlier, your research aim and research question are (or at least, should be) tightly linked. So, make sure that your research question (or set of questions) aligns with your research aim . If not, you’ll need to revise one of the two to achieve this.

FAQ: Research Questions

Research question faqs, how many research questions should i have, what should i avoid when writing a research question, can a research question be a statement.

Typically, a research question is phrased as a question, not a statement. A question clearly indicates what you’re setting out to discover.

Can a research question be too broad or too narrow?

Yes. A question that’s too broad makes your research unfocused, while a question that’s too narrow limits the scope of your study.

Here’s an example of a research question that’s too broad:

“Why is mental health important?”

Conversely, here’s an example of a research question that’s likely too narrow:

“What is the impact of sleep deprivation on the exam scores of 19-year-old males in London studying maths at The Open University?”

Can I change my research question during the research process?

How do i know if my research question is good.

A good research question is focused, specific, practical, rooted in a research gap, and aligned with the research aim. If your question meets these criteria, it’s likely a strong question.

Is a research question similar to a hypothesis?

Not quite. A hypothesis is a testable statement that predicts an outcome, while a research question is a query that you’re trying to answer through your study. Naturally, there can be linkages between a study’s research questions and hypothesis, but they serve different functions.

How are research questions and research objectives related?

The research question is a focused and specific query that your study aims to answer. It’s the central issue you’re investigating. The research objective, on the other hand, outlines the steps you’ll take to answer your research question. Research objectives are often more action-oriented and can be broken down into smaller tasks that guide your research process. In a sense, they’re something of a roadmap that helps you answer your research question.

Need some inspiration?

If you’d like to see more examples of research questions, check out our research question mega list here .  Alternatively, if you’d like 1-on-1 help developing a high-quality research question, consider our private coaching service .

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This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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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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A research question is a statement that defines what is to be studied. It is the core of the research project, study, or literature review. Your research question  focuses the study, determines the methodology, and guides all stages of inquiry, analysis, and reporting.

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Frequently asked questions

What is a research project.

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.

Frequently asked questions: Dissertation

The acknowledgements are generally included at the very beginning of your thesis or dissertation, directly after the title page and before the abstract .

If you only used a few abbreviations in your thesis or dissertation, you don’t necessarily need to include a list of abbreviations .

If your abbreviations are numerous, or if you think they won’t be known to your audience, it’s never a bad idea to add one. They can also improve readability, minimising confusion about abbreviations unfamiliar to your reader.

A list of figures and tables compiles all of the figures and tables that you used in your thesis or dissertation and displays them with the page number where they can be found.

A thesis or dissertation outline is one of the most critical first steps in your writing process. It helps you to lay out and organise your ideas and can provide you with a roadmap for deciding what kind of research you’d like to undertake.

Generally, an outline contains information on the different sections included in your thesis or dissertation, such as:

• Your anticipated title
• Your abstract
• Your chapters (sometimes subdivided into further topics like literature review, research methods, avenues for future research, etc.)

An abstract for a thesis or dissertation is usually around 150–300 words. There’s often a strict word limit, so make sure to check your university’s requirements.

The abstract appears on its own page, after the title page and acknowledgements but before the table of contents .

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

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

For a stronger dissertation conclusion , avoid including:

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

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

The conclusion of your thesis or dissertation shouldn’t take up more than 5-7% of your overall word count.

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

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

Research objectives describe what you intend your research project to accomplish.

They summarise the approach and purpose of the project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement .

Don’t feel that you have to write the introduction first. The introduction is often one of the last parts of the research paper you’ll write, along with the conclusion.

This is because it can be easier to introduce your paper once you’ve already written the body ; you may not have the clearest idea of your arguments until you’ve written them, and things can change during the writing process .

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

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

A dissertation prospectus or proposal describes what or who you plan to research for your dissertation. It delves into why, when, where, and how you will do your research, as well as helps you choose a type of research to pursue. You should also determine whether you plan to pursue qualitative or quantitative methods and what your research design will look like.

It should outline all of the decisions you have taken about your project, from your dissertation topic to your hypotheses and research objectives , ready to be approved by your supervisor or committee.

Note that some departments require a defense component, where you present your prospectus to your committee orally.

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• Research Questions: Definitions, Types + [Examples]

Research questions lie at the core of systematic investigation and this is because recording accurate research outcomes is tied to asking the right questions. Asking the right questions when conducting research can help you collect relevant and insightful information that ultimately influences your work, positively. 

The right research questions are typically easy to understand, straight to the point, and engaging. In this article, we will share tips on how to create the right research questions and also show you how to create and administer an online questionnaire with Formplus . 

What is a Research Question? 

A research question is a specific inquiry which the research seeks to provide a response to. It resides at the core of systematic investigation and it helps you to clearly define a path for the research process. 

A research question is usually the first step in any research project. Basically, it is the primary interrogation point of your research and it sets the pace for your work.  

Typically, a research question focuses on the research, determines the methodology and hypothesis, and guides all stages of inquiry, analysis, and reporting. With the right research questions, you will be able to gather useful information for your investigation. 

Types of Research Questions 

Research questions are broadly categorized into 2; that is, qualitative research questions and quantitative research questions. Qualitative and quantitative research questions can be used independently and co-dependently in line with the overall focus and objectives of your research. 

If your research aims at collecting quantifiable data , you will need to make use of quantitative research questions. On the other hand, qualitative questions help you to gather qualitative data bothering on the perceptions and observations of your research subjects. 

Qualitative Research Questions  

A qualitative research question is a type of systematic inquiry that aims at collecting qualitative data from research subjects. The aim of qualitative research questions is to gather non-statistical information pertaining to the experiences, observations, and perceptions of the research subjects in line with the objectives of the investigation. 

Types of Qualitative Research Questions  

• Ethnographic Research Questions

As the name clearly suggests, ethnographic research questions are inquiries presented in ethnographic research. Ethnographic research is a qualitative research approach that involves observing variables in their natural environments or habitats in order to arrive at objective research outcomes. 

These research questions help the researcher to gather insights into the habits, dispositions, perceptions, and behaviors of research subjects as they interact in specific environments. 

Ethnographic research questions can be used in education, business, medicine, and other fields of study, and they are very useful in contexts aimed at collecting in-depth and specific information that are peculiar to research variables. For instance, asking educational ethnographic research questions can help you understand how pedagogy affects classroom relations and behaviors. 

This type of research question can be administered physically through one-on-one interviews, naturalism (live and work), and participant observation methods. Alternatively, the researcher can ask ethnographic research questions via online surveys and questionnaires created with Formplus.  

Examples of Ethnographic Research Questions

• Why do you use this product?
• Have you noticed any side effects since you started using this drug?
• Does this product meet your needs?

• Case Studies

A case study is a qualitative research approach that involves carrying out a detailed investigation into a research subject(s) or variable(s). In the course of a case study, the researcher gathers a range of data from multiple sources of information via different data collection methods, and over a period of time. 

The aim of a case study is to analyze specific issues within definite contexts and arrive at detailed research subject analyses by asking the right questions. This research method can be explanatory, descriptive , or exploratory depending on the focus of your systematic investigation or research. 

An explanatory case study is one that seeks to gather information on the causes of real-life occurrences. This type of case study uses “how” and “why” questions in order to gather valid information about the causative factors of an event. 

Descriptive case studies are typically used in business researches, and they aim at analyzing the impact of changing market dynamics on businesses. On the other hand, exploratory case studies aim at providing answers to “who” and “what” questions using data collection tools like interviews and questionnaires. 

Some questions you can include in your case studies are: 

• Why did you choose our services?
• How has this policy affected your business output?
• What benefits have you recorded since you started using our product?

An interview is a qualitative research method that involves asking respondents a series of questions in order to gather information about a research subject. Interview questions can be close-ended or open-ended , and they prompt participants to provide valid information that is useful to the research. 

An interview may also be structured, semi-structured , or unstructured , and this further influences the types of questions they include. Structured interviews are made up of more close-ended questions because they aim at gathering quantitative data while unstructured interviews consist, primarily, of open-ended questions that allow the researcher to collect qualitative information from respondents. 

You can conduct interview research by scheduling a physical meeting with respondents, through a telephone conversation, and via digital media and video conferencing platforms like Skype and Zoom. Alternatively, you can use Formplus surveys and questionnaires for your interview. 

Examples of interview questions include: 

• What challenges did you face while using our product?
• What specific needs did our product meet?
• What would you like us to improve our service delivery?

Quantitative Research Questions

Quantitative research questions are questions that are used to gather quantifiable data from research subjects. These types of research questions are usually more specific and direct because they aim at collecting information that can be measured; that is, statistical information. 

Types of Quantitative Research Questions

• Descriptive Research Questions

Descriptive research questions are inquiries that researchers use to gather quantifiable data about the attributes and characteristics of research subjects. These types of questions primarily seek responses that reveal existing patterns in the nature of the research subjects. 

It is important to note that descriptive research questions are not concerned with the causative factors of the discovered attributes and characteristics. Rather, they focus on the “what”; that is, describing the subject of the research without paying attention to the reasons for its occurrence. 

Descriptive research questions are typically closed-ended because they aim at gathering definite and specific responses from research participants. Also, they can be used in customer experience surveys and market research to collect information about target markets and consumer behaviors. 

Descriptive Research Question Examples

• How often do you make use of our fitness application?
• How much would you be willing to pay for this product?

• Comparative Research Questions

A comparative research question is a type of quantitative research question that is used to gather information about the differences between two or more research subjects across different variables. These types of questions help the researcher to identify distinct features that mark one research subject from the other while highlighting existing similarities. 

Asking comparative research questions in market research surveys can provide insights on how your product or service matches its competitors. In addition, it can help you to identify the strengths and weaknesses of your product for a better competitive advantage.  

The 5 steps involved in the framing of comparative research questions are: 

• Choose your starting phrase
• Identify and name the dependent variable
• Identify the groups you are interested in
• Identify the appropriate adjoining text
• Write out the comparative research question

Comparative Research Question Samples 

• What are the differences between a landline telephone and a smartphone?
• What are the differences between work-from-home and on-site operations?

• Relationship-based Research Questions  

Just like the name suggests, a relationship-based research question is one that inquires into the nature of the association between two research subjects within the same demographic. These types of research questions help you to gather information pertaining to the nature of the association between two research variables. 

Relationship-based research questions are also known as correlational research questions because they seek to clearly identify the link between 2 variables. 

Read: Correlational Research Designs: Types, Examples & Methods

Examples of relationship-based research questions include: 

• What is the relationship between purchasing power and the business site?
• What is the relationship between the work environment and workforce turnover?

Examples of a Good Research Question

Since research questions lie at the core of any systematic investigations, it is important to know how to frame a good research question. The right research questions will help you to gather the most objective responses that are useful to your systematic investigation. 

A good research question is one that requires impartial responses and can be answered via existing sources of information. Also, a good research question seeks answers that actively contribute to a body of knowledge; hence, it is a question that is yet to be answered in your specific research context.

• Open-Ended Questions

 An open-ended question is a type of research question that does not restrict respondents to a set of premeditated answer options. In other words, it is a question that allows the respondent to freely express his or her perceptions and feelings towards the research subject. 

Examples of Open-ended Questions

• How do you deal with stress in the workplace?
• What is a typical day at work like for you?
• Close-ended Questions

A close-ended question is a type of survey question that restricts respondents to a set of predetermined answers such as multiple-choice questions . Close-ended questions typically require yes or no answers and are commonly used in quantitative research to gather numerical data from research participants. 

Examples of Close-ended Questions

• Did you enjoy this event?
• How likely are you to recommend our services?
• Very Likely
• Somewhat Likely
• Likert Scale Questions

A Likert scale question is a type of close-ended question that is structured as a 3-point, 5-point, or 7-point psychometric scale . This type of question is used to measure the survey respondent’s disposition towards multiple variables and it can be unipolar or bipolar in nature. 

Example of Likert Scale Questions

• How satisfied are you with our service delivery?
• Very dissatisfied
• Not satisfied
• Very satisfied
• Rating Scale Questions

A rating scale question is a type of close-ended question that seeks to associate a specific qualitative measure (rating) with the different variables in research. It is commonly used in customer experience surveys, market research surveys, employee reviews, and product evaluations. 

Example of Rating Questions

• How would you rate our service delivery?

  Examples of a Bad Research Question

Knowing what bad research questions are would help you avoid them in the course of your systematic investigation. These types of questions are usually unfocused and often result in research biases that can negatively impact the outcomes of your systematic investigation. 

• Loaded Questions

A loaded question is a question that subtly presupposes one or more unverified assumptions about the research subject or participant. This type of question typically boxes the respondent in a corner because it suggests implicit and explicit biases that prevent objective responses. 

Example of Loaded Questions

• Have you stopped smoking?
• Where did you hide the money?
• Negative Questions

A negative question is a type of question that is structured with an implicit or explicit negator. Negative questions can be misleading because they upturn the typical yes/no response order by requiring a negative answer for affirmation and an affirmative answer for negation. 

Examples of Negative Questions

• Would you mind dropping by my office later today?
• Didn’t you visit last week?
• Leading Questions  

A l eading question is a type of survey question that nudges the respondent towards an already-determined answer. It is highly suggestive in nature and typically consists of biases and unverified assumptions that point toward its premeditated responses. 

Examples of Leading Questions

• If you enjoyed this service, would you be willing to try out our other packages?
• Our product met your needs, didn’t it?

Read More: Leading Questions: Definition, Types, and Examples

How to Use Formplus as Online Research Questionnaire Tool  

With Formplus, you can create and administer your online research questionnaire easily. In the form builder, you can add different form fields to your questionnaire and edit these fields to reflect specific research questions for your systematic investigation. 

Here is a step-by-step guide on how to create an online research questionnaire with Formplus: 

• Sign in to your Formplus accoun t, then click on the “create new form” button in your dashboard to access the Form builder.

• In the form builder, add preferred form fields to your online research questionnaire by dragging and dropping them into the form. Add a title to your form in the title block. You can edit form fields by clicking on the “pencil” icon on the right corner of each form field.

• Save the form to access the customization section of the builder. Here, you can tweak the appearance of your online research questionnaire by adding background images, changing the form font, and adding your organization’s logo.

• Finally, copy your form link and share it with respondents. You can also use any of the multiple sharing options available.

Conclusion  

The success of your research starts with framing the right questions to help you collect the most valid and objective responses. Be sure to avoid bad research questions like loaded and negative questions that can be misleading and adversely affect your research data and outcomes. 

Your research questions should clearly reflect the aims and objectives of your systematic investigation while laying emphasis on specific contexts. To help you seamlessly gather responses for your research questions, you can create an online research questionnaire on Formplus.  

Connect to Formplus, Get Started Now - It's Free!

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3 The research process

In Chapter 1, we saw that scientific research is the process of acquiring scientific knowledge using the scientific method. But how is such research conducted? This chapter delves into the process of scientific research, and the assumptions and outcomes of the research process.

Paradigms of social research

Our design and conduct of research is shaped by our mental models, or frames of reference that we use to organise our reasoning and observations. These mental models or frames (belief systems) are called paradigms . The word ‘paradigm’ was popularised by Thomas Kuhn (1962) [1] in his book The structure of scientific r evolutions , where he examined the history of the natural sciences to identify patterns of activities that shape the progress of science. Similar ideas are applicable to social sciences as well, where a social reality can be viewed by different people in different ways, which may constrain their thinking and reasoning about the observed phenomenon. For instance, conservatives and liberals tend to have very different perceptions of the role of government in people’s lives, and hence, have different opinions on how to solve social problems. Conservatives may believe that lowering taxes is the best way to stimulate a stagnant economy because it increases people’s disposable income and spending, which in turn expands business output and employment. In contrast, liberals may believe that governments should invest more directly in job creation programs such as public works and infrastructure projects, which will increase employment and people’s ability to consume and drive the economy. Likewise, Western societies place greater emphasis on individual rights, such as one’s right to privacy, right of free speech, and right to bear arms. In contrast, Asian societies tend to balance the rights of individuals against the rights of families, organisations, and the government, and therefore tend to be more communal and less individualistic in their policies. Such differences in perspective often lead Westerners to criticise Asian governments for being autocratic, while Asians criticise Western societies for being greedy, having high crime rates, and creating a ‘cult of the individual’. Our personal paradigms are like ‘coloured glasses’ that govern how we view the world and how we structure our thoughts about what we see in the world.

Paradigms are often hard to recognise, because they are implicit, assumed, and taken for granted. However, recognising these paradigms is key to making sense of and reconciling differences in people’s perceptions of the same social phenomenon. For instance, why do liberals believe that the best way to improve secondary education is to hire more teachers, while conservatives believe that privatising education (using such means as school vouchers) is more effective in achieving the same goal? Conservatives place more faith in competitive markets (i.e., in free competition between schools competing for education dollars), while liberals believe more in labour (i.e., in having more teachers and schools). Likewise, in social science research, to understand why a certain technology was successfully implemented in one organisation, but failed miserably in another, a researcher looking at the world through a ‘rational lens’ will look for rational explanations of the problem, such as inadequate technology or poor fit between technology and the task context where it is being utilised. Another researcher looking at the same problem through a ‘social lens’ may seek out social deficiencies such as inadequate user training or lack of management support. Those seeing it through a ‘political lens’ will look for instances of organisational politics that may subvert the technology implementation process. Hence, subconscious paradigms often constrain the concepts that researchers attempt to measure, their observations, and their subsequent interpretations of a phenomenon. However, given the complex nature of social phenomena, it is possible that all of the above paradigms are partially correct, and that a fuller understanding of the problem may require an understanding and application of multiple paradigms.

Two popular paradigms today among social science researchers are positivism and post-positivism. Positivism , based on the works of French philosopher Auguste Comte (1798–1857), was the dominant scientific paradigm until the mid-twentieth century. It holds that science or knowledge creation should be restricted to what can be observed and measured. Positivism tends to rely exclusively on theories that can be directly tested. Though positivism was originally an attempt to separate scientific inquiry from religion (where the precepts could not be objectively observed), positivism led to empiricism or a blind faith in observed data and a rejection of any attempt to extend or reason beyond observable facts. Since human thoughts and emotions could not be directly measured, they were not considered to be legitimate topics for scientific research. Frustrations with the strictly empirical nature of positivist philosophy led to the development of post-positivism (or postmodernism) during the mid-late twentieth century. Post-positivism argues that one can make reasonable inferences about a phenomenon by combining empirical observations with logical reasoning. Post-positivists view science as not certain but probabilistic (i.e., based on many contingencies), and often seek to explore these contingencies to understand social reality better. The post-positivist camp has further fragmented into subjectivists , who view the world as a subjective construction of our subjective minds rather than as an objective reality, and critical realists , who believe that there is an external reality that is independent of a person’s thinking but we can never know such reality with any degree of certainty.

Burrell and Morgan (1979), [2] in their seminal book Sociological p aradigms and organizational a nalysis , suggested that the way social science researchers view and study social phenomena is shaped by two fundamental sets of philosophical assumptions: ontology and epistemology. Ontology refers to our assumptions about how we see the world (e.g., does the world consist mostly of social order or constant change?). Epistemology refers to our assumptions about the best way to study the world (e.g., should we use an objective or subjective approach to study social reality?). Using these two sets of assumptions, we can categorise social science research as belonging to one of four categories (see Figure 3.1).

If researchers view the world as consisting mostly of social order (ontology) and hence seek to study patterns of ordered events or behaviours, and believe that the best way to study such a world is using an objective approach (epistemology) that is independent of the person conducting the observation or interpretation, such as by using standardised data collection tools like surveys, then they are adopting a paradigm of functionalism . However, if they believe that the best way to study social order is though the subjective interpretation of participants, such as by interviewing different participants and reconciling differences among their responses using their own subjective perspectives, then they are employing an interpretivism paradigm. If researchers believe that the world consists of radical change and seek to understand or enact change using an objectivist approach, then they are employing a radical structuralism paradigm. If they wish to understand social change using the subjective perspectives of the participants involved, then they are following a radical humanism paradigm.

To date, the majority of social science research has emulated the natural sciences, and followed the functionalist paradigm. Functionalists believe that social order or patterns can be understood in terms of their functional components, and therefore attempt to break down a problem into small components and studying one or more components in detail using objectivist techniques such as surveys and experimental research. However, with the emergence of post-positivist thinking, a small but growing number of social science researchers are attempting to understand social order using subjectivist techniques such as interviews and ethnographic studies. Radical humanism and radical structuralism continues to represent a negligible proportion of social science research, because scientists are primarily concerned with understanding generalisable patterns of behaviour, events, or phenomena, rather than idiosyncratic or changing events. Nevertheless, if you wish to study social change, such as why democratic movements are increasingly emerging in Middle Eastern countries, or why this movement was successful in Tunisia, took a longer path to success in Libya, and is still not successful in Syria, then perhaps radical humanism is the right approach for such a study. Social and organisational phenomena generally consist of elements of both order and change. For instance, organisational success depends on formalised business processes, work procedures, and job responsibilities, while being simultaneously constrained by a constantly changing mix of competitors, competing products, suppliers, and customer base in the business environment. Hence, a holistic and more complete understanding of social phenomena such as why some organisations are more successful than others, requires an appreciation and application of a multi-paradigmatic approach to research.

Overview of the research process

So how do our mental paradigms shape social science research? At its core, all scientific research is an iterative process of observation, rationalisation, and validation. In the observation phase, we observe a natural or social phenomenon, event, or behaviour that interests us. In the rationalisation phase, we try to make sense of the observed phenomenon, event, or behaviour by logically connecting the different pieces of the puzzle that we observe, which in some cases, may lead to the construction of a theory. Finally, in the validation phase, we test our theories using a scientific method through a process of data collection and analysis, and in doing so, possibly modify or extend our initial theory. However, research designs vary based on whether the researcher starts at observation and attempts to rationalise the observations (inductive research), or whether the researcher starts at an ex ante rationalisation or a theory and attempts to validate the theory (deductive research). Hence, the observation-rationalisation-validation cycle is very similar to the induction-deduction cycle of research discussed in Chapter 1.

Most traditional research tends to be deductive and functionalistic in nature. Figure 3.2 provides a schematic view of such a research project. This figure depicts a series of activities to be performed in functionalist research, categorised into three phases: exploration, research design, and research execution. Note that this generalised design is not a roadmap or flowchart for all research. It applies only to functionalistic research, and it can and should be modified to fit the needs of a specific project.

The first phase of research is exploration . This phase includes exploring and selecting research questions for further investigation, examining the published literature in the area of inquiry to understand the current state of knowledge in that area, and identifying theories that may help answer the research questions of interest.

The first step in the exploration phase is identifying one or more research questions dealing with a specific behaviour, event, or phenomena of interest. Research questions are specific questions about a behaviour, event, or phenomena of interest that you wish to seek answers for in your research. Examples include determining which factors motivate consumers to purchase goods and services online without knowing the vendors of these goods or services, how can we make high school students more creative, and why some people commit terrorist acts. Research questions can delve into issues of what, why, how, when, and so forth. More interesting research questions are those that appeal to a broader population (e.g., ‘how can firms innovate?’ is a more interesting research question than ‘how can Chinese firms innovate in the service-sector?’), address real and complex problems (in contrast to hypothetical or ‘toy’ problems), and where the answers are not obvious. Narrowly focused research questions (often with a binary yes/no answer) tend to be less useful and less interesting and less suited to capturing the subtle nuances of social phenomena. Uninteresting research questions generally lead to uninteresting and unpublishable research findings.

The next step is to conduct a literature review of the domain of interest. The purpose of a literature review is three-fold: one, to survey the current state of knowledge in the area of inquiry, two, to identify key authors, articles, theories, and findings in that area, and three, to identify gaps in knowledge in that research area. Literature review is commonly done today using computerised keyword searches in online databases. Keywords can be combined using Boolean operators such as ‘and’ and ‘or’ to narrow down or expand the search results. Once a shortlist of relevant articles is generated from the keyword search, the researcher must then manually browse through each article, or at least its abstract, to determine the suitability of that article for a detailed review. Literature reviews should be reasonably complete, and not restricted to a few journals, a few years, or a specific methodology. Reviewed articles may be summarised in the form of tables, and can be further structured using organising frameworks such as a concept matrix. A well-conducted literature review should indicate whether the initial research questions have already been addressed in the literature (which would obviate the need to study them again), whether there are newer or more interesting research questions available, and whether the original research questions should be modified or changed in light of the findings of the literature review. The review can also provide some intuitions or potential answers to the questions of interest and/or help identify theories that have previously been used to address similar questions.

Since functionalist (deductive) research involves theory-testing, the third step is to identify one or more theories can help address the desired research questions. While the literature review may uncover a wide range of concepts or constructs potentially related to the phenomenon of interest, a theory will help identify which of these constructs is logically relevant to the target phenomenon and how. Forgoing theories may result in measuring a wide range of less relevant, marginally relevant, or irrelevant constructs, while also minimising the chances of obtaining results that are meaningful and not by pure chance. In functionalist research, theories can be used as the logical basis for postulating hypotheses for empirical testing. Obviously, not all theories are well-suited for studying all social phenomena. Theories must be carefully selected based on their fit with the target problem and the extent to which their assumptions are consistent with that of the target problem. We will examine theories and the process of theorising in detail in the next chapter.

The next phase in the research process is research design . This process is concerned with creating a blueprint of the actions to take in order to satisfactorily answer the research questions identified in the exploration phase. This includes selecting a research method, operationalising constructs of interest, and devising an appropriate sampling strategy.

Operationalisation is the process of designing precise measures for abstract theoretical constructs. This is a major problem in social science research, given that many of the constructs, such as prejudice, alienation, and liberalism are hard to define, let alone measure accurately. Operationalisation starts with specifying an ‘operational definition’ (or ‘conceptualization’) of the constructs of interest. Next, the researcher can search the literature to see if there are existing pre-validated measures matching their operational definition that can be used directly or modified to measure their constructs of interest. If such measures are not available or if existing measures are poor or reflect a different conceptualisation than that intended by the researcher, new instruments may have to be designed for measuring those constructs. This means specifying exactly how exactly the desired construct will be measured (e.g., how many items, what items, and so forth). This can easily be a long and laborious process, with multiple rounds of pre-tests and modifications before the newly designed instrument can be accepted as ‘scientifically valid’. We will discuss operationalisation of constructs in a future chapter on measurement.

Simultaneously with operationalisation, the researcher must also decide what research method they wish to employ for collecting data to address their research questions of interest. Such methods may include quantitative methods such as experiments or survey research or qualitative methods such as case research or action research, or possibly a combination of both. If an experiment is desired, then what is the experimental design? If this is a survey, do you plan a mail survey, telephone survey, web survey, or a combination? For complex, uncertain, and multifaceted social phenomena, multi-method approaches may be more suitable, which may help leverage the unique strengths of each research method and generate insights that may not be obtained using a single method.

Researchers must also carefully choose the target population from which they wish to collect data, and a sampling strategy to select a sample from that population. For instance, should they survey individuals or firms or workgroups within firms? What types of individuals or firms do they wish to target? Sampling strategy is closely related to the unit of analysis in a research problem. While selecting a sample, reasonable care should be taken to avoid a biased sample (e.g., sample based on convenience) that may generate biased observations. Sampling is covered in depth in a later chapter.

At this stage, it is often a good idea to write a research proposal detailing all of the decisions made in the preceding stages of the research process and the rationale behind each decision. This multi-part proposal should address what research questions you wish to study and why, the prior state of knowledge in this area, theories you wish to employ along with hypotheses to be tested, how you intend to measure constructs, what research method is to be employed and why, and desired sampling strategy. Funding agencies typically require such a proposal in order to select the best proposals for funding. Even if funding is not sought for a research project, a proposal may serve as a useful vehicle for seeking feedback from other researchers and identifying potential problems with the research project (e.g., whether some important constructs were missing from the study) before starting data collection. This initial feedback is invaluable because it is often too late to correct critical problems after data is collected in a research study.

Having decided who to study (subjects), what to measure (concepts), and how to collect data (research method), the researcher is now ready to proceed to the research execution phase. This includes pilot testing the measurement instruments, data collection, and data analysis.

Pilot testing is an often overlooked but extremely important part of the research process. It helps detect potential problems in your research design and/or instrumentation (e.g., whether the questions asked are intelligible to the targeted sample), and to ensure that the measurement instruments used in the study are reliable and valid measures of the constructs of interest. The pilot sample is usually a small subset of the target population. After successful pilot testing, the researcher may then proceed with data collection using the sampled population. The data collected may be quantitative or qualitative, depending on the research method employed.

Following data collection, the data is analysed and interpreted for the purpose of drawing conclusions regarding the research questions of interest. Depending on the type of data collected (quantitative or qualitative), data analysis may be quantitative (e.g., employ statistical techniques such as regression or structural equation modelling) or qualitative (e.g., coding or content analysis).

The final phase of research involves preparing the final research report documenting the entire research process and its findings in the form of a research paper, dissertation, or monograph. This report should outline in detail all the choices made during the research process (e.g., theory used, constructs selected, measures used, research methods, sampling, etc.) and why, as well as the outcomes of each phase of the research process. The research process must be described in sufficient detail so as to allow other researchers to replicate your study, test the findings, or assess whether the inferences derived are scientifically acceptable. Of course, having a ready research proposal will greatly simplify and quicken the process of writing the finished report. Note that research is of no value unless the research process and outcomes are documented for future generations—such documentation is essential for the incremental progress of science.

Common mistakes in research

The research process is fraught with problems and pitfalls, and novice researchers often find, after investing substantial amounts of time and effort into a research project, that their research questions were not sufficiently answered, or that the findings were not interesting enough, or that the research was not of ‘acceptable’ scientific quality. Such problems typically result in research papers being rejected by journals. Some of the more frequent mistakes are described below.

Insufficiently motivated research questions. Often times, we choose our ‘pet’ problems that are interesting to us but not to the scientific community at large, i.e., it does not generate new knowledge or insight about the phenomenon being investigated. Because the research process involves a significant investment of time and effort on the researcher’s part, the researcher must be certain—and be able to convince others—that the research questions they seek to answer deal with real—and not hypothetical—problems that affect a substantial portion of a population and have not been adequately addressed in prior research.

Pursuing research fads. Another common mistake is pursuing ‘popular’ topics with limited shelf life. A typical example is studying technologies or practices that are popular today. Because research takes several years to complete and publish, it is possible that popular interest in these fads may die down by the time the research is completed and submitted for publication. A better strategy may be to study ‘timeless’ topics that have always persisted through the years.

Unresearchable problems. Some research problems may not be answered adequately based on observed evidence alone, or using currently accepted methods and procedures. Such problems are best avoided. However, some unresearchable, ambiguously defined problems may be modified or fine tuned into well-defined and useful researchable problems.

Favoured research methods. Many researchers have a tendency to recast a research problem so that it is amenable to their favourite research method (e.g., survey research). This is an unfortunate trend. Research methods should be chosen to best fit a research problem, and not the other way around.

Blind data mining. Some researchers have the tendency to collect data first (using instruments that are already available), and then figure out what to do with it. Note that data collection is only one step in a long and elaborate process of planning, designing, and executing research. In fact, a series of other activities are needed in a research process prior to data collection. If researchers jump into data collection without such elaborate planning, the data collected will likely be irrelevant, imperfect, or useless, and their data collection efforts may be entirely wasted. An abundance of data cannot make up for deficits in research planning and design, and particularly, for the lack of interesting research questions.

• Kuhn, T. (1962). The structure of scientific revolutions . Chicago: University of Chicago Press. ↵
• Burrell, G. & Morgan, G. (1979). Sociological paradigms and organisational analysis: elements of the sociology of corporate life . London: Heinemann Educational. ↵

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

• Provide an overview of the research problem and the need for a research methodology section
• Outline the main research questions and objectives

II. Research Design

• Explain the research design chosen and why it is appropriate for the research question(s) and objectives
• Discuss any alternative research designs considered and why they were not chosen
• Describe the research setting and participants (if applicable)

III. Data Collection Methods

• Describe the methods used to collect data (e.g., surveys, interviews, observations)
• Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

• Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
• Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or software used for data analysis

V. Ethical Considerations

• Discuss any ethical issues that may arise from the research and how they were addressed
• Explain how informed consent was obtained (if applicable)
• Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

• Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

• Summarize the key aspects of the research methodology section
• Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

• Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
• Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
• Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
• Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
• Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
• Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
• Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
• Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

• To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
• To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
• To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
• To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
• To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
• To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
• To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
• To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
• To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

• To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
• To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
• To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
• To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
• To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

• Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
• Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
• Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
• Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
• Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
• Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
• Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
• Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

About the author.

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• v.53(4); 2010 Aug

Research questions, hypotheses and objectives

Patricia farrugia.

* Michael G. DeGroote School of Medicine, the

Bradley A. Petrisor

† Division of Orthopaedic Surgery and the

Forough Farrokhyar

‡ Departments of Surgery and

§ Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ont

Mohit Bhandari

There is an increasing familiarity with the principles of evidence-based medicine in the surgical community. As surgeons become more aware of the hierarchy of evidence, grades of recommendations and the principles of critical appraisal, they develop an increasing familiarity with research design. Surgeons and clinicians are looking more and more to the literature and clinical trials to guide their practice; as such, it is becoming a responsibility of the clinical research community to attempt to answer questions that are not only well thought out but also clinically relevant. The development of the research question, including a supportive hypothesis and objectives, is a necessary key step in producing clinically relevant results to be used in evidence-based practice. A well-defined and specific research question is more likely to help guide us in making decisions about study design and population and subsequently what data will be collected and analyzed. 1

Objectives of this article

In this article, we discuss important considerations in the development of a research question and hypothesis and in defining objectives for research. By the end of this article, the reader will be able to appreciate the significance of constructing a good research question and developing hypotheses and research objectives for the successful design of a research study. The following article is divided into 3 sections: research question, research hypothesis and research objectives.

Research question

Interest in a particular topic usually begins the research process, but it is the familiarity with the subject that helps define an appropriate research question for a study. 1 Questions then arise out of a perceived knowledge deficit within a subject area or field of study. 2 Indeed, Haynes suggests that it is important to know “where the boundary between current knowledge and ignorance lies.” 1 The challenge in developing an appropriate research question is in determining which clinical uncertainties could or should be studied and also rationalizing the need for their investigation.

Increasing one’s knowledge about the subject of interest can be accomplished in many ways. Appropriate methods include systematically searching the literature, in-depth interviews and focus groups with patients (and proxies) and interviews with experts in the field. In addition, awareness of current trends and technological advances can assist with the development of research questions. 2 It is imperative to understand what has been studied about a topic to date in order to further the knowledge that has been previously gathered on a topic. Indeed, some granting institutions (e.g., Canadian Institute for Health Research) encourage applicants to conduct a systematic review of the available evidence if a recent review does not already exist and preferably a pilot or feasibility study before applying for a grant for a full trial.

In-depth knowledge about a subject may generate a number of questions. It then becomes necessary to ask whether these questions can be answered through one study or if more than one study needed. 1 Additional research questions can be developed, but several basic principles should be taken into consideration. 1 All questions, primary and secondary, should be developed at the beginning and planning stages of a study. Any additional questions should never compromise the primary question because it is the primary research question that forms the basis of the hypothesis and study objectives. It must be kept in mind that within the scope of one study, the presence of a number of research questions will affect and potentially increase the complexity of both the study design and subsequent statistical analyses, not to mention the actual feasibility of answering every question. 1 A sensible strategy is to establish a single primary research question around which to focus the study plan. 3 In a study, the primary research question should be clearly stated at the end of the introduction of the grant proposal, and it usually specifies the population to be studied, the intervention to be implemented and other circumstantial factors. 4

Hulley and colleagues 2 have suggested the use of the FINER criteria in the development of a good research question ( Box 1 ). The FINER criteria highlight useful points that may increase the chances of developing a successful research project. A good research question should specify the population of interest, be of interest to the scientific community and potentially to the public, have clinical relevance and further current knowledge in the field (and of course be compliant with the standards of ethical boards and national research standards).

FINER criteria for a good research question

Adapted with permission from Wolters Kluwer Health. 2

Whereas the FINER criteria outline the important aspects of the question in general, a useful format to use in the development of a specific research question is the PICO format — consider the population (P) of interest, the intervention (I) being studied, the comparison (C) group (or to what is the intervention being compared) and the outcome of interest (O). 3 , 5 , 6 Often timing (T) is added to PICO ( Box 2 ) — that is, “Over what time frame will the study take place?” 1 The PICOT approach helps generate a question that aids in constructing the framework of the study and subsequently in protocol development by alluding to the inclusion and exclusion criteria and identifying the groups of patients to be included. Knowing the specific population of interest, intervention (and comparator) and outcome of interest may also help the researcher identify an appropriate outcome measurement tool. 7 The more defined the population of interest, and thus the more stringent the inclusion and exclusion criteria, the greater the effect on the interpretation and subsequent applicability and generalizability of the research findings. 1 , 2 A restricted study population (and exclusion criteria) may limit bias and increase the internal validity of the study; however, this approach will limit external validity of the study and, thus, the generalizability of the findings to the practical clinical setting. Conversely, a broadly defined study population and inclusion criteria may be representative of practical clinical practice but may increase bias and reduce the internal validity of the study.

PICOT criteria 1

A poorly devised research question may affect the choice of study design, potentially lead to futile situations and, thus, hamper the chance of determining anything of clinical significance, which will then affect the potential for publication. Without devoting appropriate resources to developing the research question, the quality of the study and subsequent results may be compromised. During the initial stages of any research study, it is therefore imperative to formulate a research question that is both clinically relevant and answerable.

Research hypothesis

The primary research question should be driven by the hypothesis rather than the data. 1 , 2 That is, the research question and hypothesis should be developed before the start of the study. This sounds intuitive; however, if we take, for example, a database of information, it is potentially possible to perform multiple statistical comparisons of groups within the database to find a statistically significant association. This could then lead one to work backward from the data and develop the “question.” This is counterintuitive to the process because the question is asked specifically to then find the answer, thus collecting data along the way (i.e., in a prospective manner). Multiple statistical testing of associations from data previously collected could potentially lead to spuriously positive findings of association through chance alone. 2 Therefore, a good hypothesis must be based on a good research question at the start of a trial and, indeed, drive data collection for the study.

The research or clinical hypothesis is developed from the research question and then the main elements of the study — sampling strategy, intervention (if applicable), comparison and outcome variables — are summarized in a form that establishes the basis for testing, statistical and ultimately clinical significance. 3 For example, in a research study comparing computer-assisted acetabular component insertion versus freehand acetabular component placement in patients in need of total hip arthroplasty, the experimental group would be computer-assisted insertion and the control/conventional group would be free-hand placement. The investigative team would first state a research hypothesis. This could be expressed as a single outcome (e.g., computer-assisted acetabular component placement leads to improved functional outcome) or potentially as a complex/composite outcome; that is, more than one outcome (e.g., computer-assisted acetabular component placement leads to both improved radiographic cup placement and improved functional outcome).

However, when formally testing statistical significance, the hypothesis should be stated as a “null” hypothesis. 2 The purpose of hypothesis testing is to make an inference about the population of interest on the basis of a random sample taken from that population. The null hypothesis for the preceding research hypothesis then would be that there is no difference in mean functional outcome between the computer-assisted insertion and free-hand placement techniques. After forming the null hypothesis, the researchers would form an alternate hypothesis stating the nature of the difference, if it should appear. The alternate hypothesis would be that there is a difference in mean functional outcome between these techniques. At the end of the study, the null hypothesis is then tested statistically. If the findings of the study are not statistically significant (i.e., there is no difference in functional outcome between the groups in a statistical sense), we cannot reject the null hypothesis, whereas if the findings were significant, we can reject the null hypothesis and accept the alternate hypothesis (i.e., there is a difference in mean functional outcome between the study groups), errors in testing notwithstanding. In other words, hypothesis testing confirms or refutes the statement that the observed findings did not occur by chance alone but rather occurred because there was a true difference in outcomes between these surgical procedures. The concept of statistical hypothesis testing is complex, and the details are beyond the scope of this article.

Another important concept inherent in hypothesis testing is whether the hypotheses will be 1-sided or 2-sided. A 2-sided hypothesis states that there is a difference between the experimental group and the control group, but it does not specify in advance the expected direction of the difference. For example, we asked whether there is there an improvement in outcomes with computer-assisted surgery or whether the outcomes worse with computer-assisted surgery. We presented a 2-sided test in the above example because we did not specify the direction of the difference. A 1-sided hypothesis states a specific direction (e.g., there is an improvement in outcomes with computer-assisted surgery). A 2-sided hypothesis should be used unless there is a good justification for using a 1-sided hypothesis. As Bland and Atlman 8 stated, “One-sided hypothesis testing should never be used as a device to make a conventionally nonsignificant difference significant.”

The research hypothesis should be stated at the beginning of the study to guide the objectives for research. Whereas the investigators may state the hypothesis as being 1-sided (there is an improvement with treatment), the study and investigators must adhere to the concept of clinical equipoise. According to this principle, a clinical (or surgical) trial is ethical only if the expert community is uncertain about the relative therapeutic merits of the experimental and control groups being evaluated. 9 It means there must exist an honest and professional disagreement among expert clinicians about the preferred treatment. 9

Designing a research hypothesis is supported by a good research question and will influence the type of research design for the study. Acting on the principles of appropriate hypothesis development, the study can then confidently proceed to the development of the research objective.

Research objective

The primary objective should be coupled with the hypothesis of the study. Study objectives define the specific aims of the study and should be clearly stated in the introduction of the research protocol. 7 From our previous example and using the investigative hypothesis that there is a difference in functional outcomes between computer-assisted acetabular component placement and free-hand placement, the primary objective can be stated as follows: this study will compare the functional outcomes of computer-assisted acetabular component insertion versus free-hand placement in patients undergoing total hip arthroplasty. Note that the study objective is an active statement about how the study is going to answer the specific research question. Objectives can (and often do) state exactly which outcome measures are going to be used within their statements. They are important because they not only help guide the development of the protocol and design of study but also play a role in sample size calculations and determining the power of the study. 7 These concepts will be discussed in other articles in this series.

From the surgeon’s point of view, it is important for the study objectives to be focused on outcomes that are important to patients and clinically relevant. For example, the most methodologically sound randomized controlled trial comparing 2 techniques of distal radial fixation would have little or no clinical impact if the primary objective was to determine the effect of treatment A as compared to treatment B on intraoperative fluoroscopy time. However, if the objective was to determine the effect of treatment A as compared to treatment B on patient functional outcome at 1 year, this would have a much more significant impact on clinical decision-making. Second, more meaningful surgeon–patient discussions could ensue, incorporating patient values and preferences with the results from this study. 6 , 7 It is the precise objective and what the investigator is trying to measure that is of clinical relevance in the practical setting.

The following is an example from the literature about the relation between the research question, hypothesis and study objectives:

Study: Warden SJ, Metcalf BR, Kiss ZS, et al. Low-intensity pulsed ultrasound for chronic patellar tendinopathy: a randomized, double-blind, placebo-controlled trial. Rheumatology 2008;47:467–71.

Research question: How does low-intensity pulsed ultrasound (LIPUS) compare with a placebo device in managing the symptoms of skeletally mature patients with patellar tendinopathy?

Research hypothesis: Pain levels are reduced in patients who receive daily active-LIPUS (treatment) for 12 weeks compared with individuals who receive inactive-LIPUS (placebo).

Objective: To investigate the clinical efficacy of LIPUS in the management of patellar tendinopathy symptoms.

The development of the research question is the most important aspect of a research project. A research project can fail if the objectives and hypothesis are poorly focused and underdeveloped. Useful tips for surgical researchers are provided in Box 3 . Designing and developing an appropriate and relevant research question, hypothesis and objectives can be a difficult task. The critical appraisal of the research question used in a study is vital to the application of the findings to clinical practice. Focusing resources, time and dedication to these 3 very important tasks will help to guide a successful research project, influence interpretation of the results and affect future publication efforts.

Tips for developing research questions, hypotheses and objectives for research studies

• Perform a systematic literature review (if one has not been done) to increase knowledge and familiarity with the topic and to assist with research development.
• Learn about current trends and technological advances on the topic.
• Seek careful input from experts, mentors, colleagues and collaborators to refine your research question as this will aid in developing the research question and guide the research study.
• Use the FINER criteria in the development of the research question.
• Ensure that the research question follows PICOT format.
• Develop a research hypothesis from the research question.
• Develop clear and well-defined primary and secondary (if needed) objectives.
• Ensure that the research question and objectives are answerable, feasible and clinically relevant.

FINER = feasible, interesting, novel, ethical, relevant; PICOT = population (patients), intervention (for intervention studies only), comparison group, outcome of interest, time.

Competing interests: No funding was received in preparation of this paper. Dr. Bhandari was funded, in part, by a Canada Research Chair, McMaster University.

Chapter 2: Psychological Research

Descriptive research.

Psychologists use descriptive, experimental, and correlational methods to conduct research. Descriptive, or qualitative, methods include the case study, naturalistic observation, surveys, archival research, longitudinal research, and cross-sectional research.

https://assessments.lumenlearning.com/assessments/2706

There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions to extensive, in-depth interviews—to well-controlled experiments.

The three main categories of psychological research are descriptive, correlational, and experimental research. Research studies that do not test specific relationships between variables are called descriptive, or qualitative, studies . These studies are used to describe general or specific behaviors and attributes that are observed and measured. In the early stages of research it might be difficult to form a hypothesis, especially when there is not any existing literature in the area. In these situations designing an experiment would be premature, as the question of interest is not yet clearly defined as a hypothesis. Often a researcher will begin with a non-experimental approach, such as a descriptive study, to gather more information about the topic before designing an experiment or correlational study to address a specific hypothesis.

Video 1.  Descriptive Research Design  provides explanation and examples for quantitative descriptive research. A closed-captioned version of this video is available here .

Descriptive research is distinct from correlational research , in which psychologists formally test whether a relationship exists between two or more variables. Experimental research goes a step further beyond descriptive and correlational research and randomly assigns people to different conditions, using hypothesis testing to make inferences about how these conditions affect behavior. It aims to determine if one variable directly impacts and causes another. Correlational and experimental research both typically use hypothesis testing, whereas descriptive research does not.

Each of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected.

Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later in the text, there is a tremendous amount of control over variables of interest. While this is a powerful approach, experiments are often conducted in very artificial settings. This calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.

Data Collection

Regardless of the method of research, data collection will be necessary. The method of data collection selected will primarily depend on the type of information the researcher needs for their study; however, other factors, such as time, resources, and even ethical considerations can influence the selection of a data collection method. All of these factors need to be considered when selecting a data collection method because each method has unique strengths and weaknesses. We will discuss the uses and assessment of the most common data collection methods: observation, surveys, archival data, and tests.

Observation

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?

This is very similar to the phenomenon mentioned earlier in this module: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about handwashing, we have other options available to us.

Suppose we send a classmate into the restroom to actually watch whether everyone washes their hands after using the restroom. Will our observer blend into the restroom environment by wearing a white lab coat, sitting with a clipboard, and staring at the sinks? We want our researcher to be inconspicuous—perhaps standing at one of the sinks pretending to put in contact lenses while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).

Figure 1 . Seeing a police car behind you would probably affect your driving behavior. (credit: Michael Gil)

It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. If you have any doubt about this, ask yourself how your driving behavior might differ in two situations: In the first situation, you are driving down a deserted highway during the middle of the day; in the second situation, you are being followed by a police car down the same deserted highway (Figure 1).

It should be pointed out that naturalistic observation is not limited to research involving humans. Indeed, some of the best-known examples of naturalistic observation involve researchers going into the field to observe various kinds of animals in their own environments. As with human studies, the researchers maintain their distance and avoid interfering with the animal subjects so as not to influence their natural behaviors. Scientists have used this technique to study social hierarchies and interactions among animals ranging from ground squirrels to gorillas. The information provided by these studies is invaluable in understanding how those animals organize socially and communicate with one another. The anthropologist Jane Goodall, for example, spent nearly five decades observing the behavior of chimpanzees in Africa (Figure 2). As an illustration of the types of concerns that a researcher might encounter in naturalistic observation, some scientists criticized Goodall for giving the chimps names instead of referring to them by numbers—using names was thought to undermine the emotional detachment required for the objectivity of the study (McKie, 2010).

Figure 2 . (a) Jane Goodall made a career of conducting naturalistic observations of (b) chimpanzee behavior. (credit “Jane Goodall”: modification of work by Erik Hersman; “chimpanzee”: modification of work by “Afrika Force”/Flickr.com)

The greatest benefit of naturalistic observation is the validity, or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people or animals modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.

The major downside of naturalistic observation is that they are often difficult to set up and control. In our restroom study, what if you stood in the restroom all day prepared to record people’s handwashing behavior and no one came in? Or, what if you have been closely observing a troop of gorillas for weeks only to find that they migrated to a new place while you were sleeping in your tent? The benefit of realistic data comes at a cost. As a researcher, you have no control of when (or if) you have behavior to observe. In addition, this type of observational research often requires significant investments of time, money, and a good dose of luck.

Sometimes studies involve structured observation. In these cases, people are observed while engaging in set, specific tasks. An excellent example of structured observation comes from Strange Situation by Mary Ainsworth (you will read more about this in the module on lifespan development). The Strange Situation is a procedure used to evaluate attachment styles that exist between an infant and caregiver. In this scenario, caregivers bring their infants into a room filled with toys. The Strange Situation involves a number of phases, including a stranger coming into the room, the caregiver leaving the room, and the caregiver’s return to the room. The infant’s behavior is closely monitored at each phase, but it is the behavior of the infant upon being reunited with the caregiver that is most telling in terms of characterizing the infant’s attachment style with the caregiver.

Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally (Figure 3). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.

Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population.

Figure 3 . Surveys can be administered in a number of ways, including electronically administered research, like the survey shown here. (credit: Robert Nyman)

There is both strength and weakness of the survey in comparison to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.

Another potential weakness of surveys is something we touched on earlier in this module: people don’t always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.

Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the US Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).

Archival Data and Case Studies

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships.

For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and calculate how long it took them to complete their degrees, as well as course loads, grades, and extracurricular involvement. Archival research could provide important information about who is most likely to complete their education, and it could help identify important risk factors for struggling students (Figure 4).

Figure 4 . A researcher doing archival research examines records, whether archived as a (a) hardcopy or (b) electronically. (credit “paper files”: modification of work by “Newtown graffiti”/Flickr; “computer”: modification of work by INPIVIC Family/Flickr)

In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected. Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic.

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A good test will aid researchers in assessing a particular psychological construct. What is a good test? Researchers want a test that is standardized, reliable, and valid. A standardized test is one that is administered, scored, and analyzed in the same way for each participant. This minimizes differences in test scores due to confounding factors, such as variability in the testing environment or scoring process, and assures that scores are comparable. Reliability refers to the consistency of a measure. Researchers consider three types of consistency: over time (test-retest reliability), across items (internal consistency), and across different researchers (interrater reliability). Validity is the extent to which the scores from a measure represent the variable they are intended to. When a measure has good test-retest reliability and internal consistency, researchers should be more confident that the scores represent what they are supposed to.

There are various types of tests used in psychological research. Self-report measures are those in which participants report on their own thoughts, feelings, and actions, such as the Rosenberg Self-Esteem Scale or the Big Five Personality Test. Some tests measure performance, ability, aptitude, or skill, like the Stanford-Binet Intelligence Scale or the SATs.There are also tests that measure physiological states, including electrical activity or blood flow in the brain.

Video 2.  Methods of Data Collection  explains various means for gathering data for quantitative and qualitative research. A closed-captioned version of this video is available here .

Studying Changes over Time

Sometimes, especially in developmental research, the researcher is interested in examining changes over time and will need to consider a research design that will capture these changes. Remember,  research methods  are tools that are used to collect information, while r esearch design  is the strategy or blueprint for deciding how to collect and analyze information. Research design dictates which methods are used and how. There are three types of developmental research designs: cross-sectional, longitudinal, and sequential.

Video 3.  Developmental Research Designs

Cross-Sectional Design

The majority of developmental studies use cross-sectional designs because they are less time-consuming and less expensive than other developmental designs.  Cross-sectional research  designs are used to examine behavior in participants of different ages who are tested at the same point in time. Let’s suppose that researchers are interested in the relationship between intelligence and aging. They might have a hypothesis that intelligence declines as people get older. The researchers might choose to give a particular intelligence test to individuals who are 20 years old, individuals who are 50 years old, and individuals who are 80 years old at the same time and compare the data from each age group. This research is cross-sectional in design because the researchers plan to examine the intelligence scores of individuals of different ages within the same study at the same time; they are taking a “cross-section” of people at one point in time. Let’s say that the comparisons find that the 80-year-old adults score lower on the intelligence test than the 50-year-old adults, and the 50-year-old adults score lower on the intelligence test than the 20-year-old adults. Based on these data, the researchers might conclude that individuals become less intelligent as they get older. Would that be a valid (accurate) interpretation of the results?

Figure 5. Example of cross-sectional research design

No, that would not be a valid conclusion because the researchers did not follow individuals as they aged from 20 to 50 to 80 years old. One of the primary limitations of cross-sectional research is that the results yield information about age  differences  not necessarily  changes  over time. That is, although the study described above can show that the 80-year-olds scored lower on the intelligence test than the 50-year-olds, and the 50-year-olds scored lower than the 20-year-olds, the data used for this conclusion were collected from different individuals (or groups). It could be, for instance, that when these 20-year-olds get older, they will still score just as high on the intelligence test as they did at age 20. Similarly, maybe the 80-year-olds would have scored relatively low on the intelligence test when they were young; the researchers don’t know for certain because they did not follow the same individuals as they got older.

With each cohort being members of a different generation, it is also possible that the differences found between the groups are not due to age, per se, but due to cohort effects. Differences between these cohorts’ IQ results could be due to differences in life experiences specific to their generation, such as differences in education, economic conditions, advances in technology, or changes in health and nutrition standards, and not due to age-related changes.

Another disadvantage of cross-sectional research is that it is limited to one time of measurement. Data are collected at one point in time, and it’s possible that something could have happened in that year in history that affected all of the participants, although possibly each cohort may have been affected differently.

Longitudinal Research Design

Longitudinal research designs are used to examine behavior in the same individuals over time. For instance, with our example of studying intelligence and aging, a researcher might conduct a longitudinal study to examine whether 20-year-olds become less intelligent with age over time. To this end, a researcher might give an intelligence test to individuals when they are 20 years old, again when they are 50 years old, and then again when they are 80 years old. This study is longitudinal in nature because the researcher plans to study the same individuals as they age. Based on these data, the pattern of intelligence and age might look different than from the cross-sectional research; it might be found that participants’ intelligence scores are higher at age 50 than at age 20 and then remain stable or decline a little by age 80. How can that be when cross-sectional research revealed declines in intelligence with age?

Figure 6. Example of a longitudinal research design

Since longitudinal research happens over a period of time (which could be short term, as in months, but is often longer, as in years), there is a risk of attrition.  Attrition  occurs when participants fail to complete all portions of a study. Participants may move, change their phone numbers, die, or simply become disinterested in participating over time. Researchers should account for the possibility of attrition by enrolling a larger sample into their study initially, as some participants will likely drop out over time. There is also something known as  selective attrition— this means that certain groups of individuals may tend to drop out. It is often the least healthy, least educated, and lower socioeconomic participants who tend to drop out over time. That means that the remaining participants may no longer be representative of the whole population, as they are, in general, healthier, better educated, and have more money. This could be a factor in why our hypothetical research found a more optimistic picture of intelligence and aging as the years went by. What can researchers do about selective attrition? At each time of testing, they could randomly recruit more participants from the same cohort as the original members to replace those who have dropped out.

The results from longitudinal studies may also be impacted by repeated assessments. Consider how well you would do on a math test if you were given the exact same exam every day for a week. Your performance would likely improve over time, not necessarily because you developed better math abilities, but because you were continuously practicing the same math problems. This phenomenon is known as a practice effect. Practice effects occur when participants become better at a task over time because they have done it again and again (not due to natural psychological development). So our participants may have become familiar with the intelligence test each time (and with the computerized testing administration).

Another limitation of longitudinal research is that the data are limited to only one cohort. As an example, think about how comfortable the participants in the 2010 cohort of 20-year-olds are with computers. Since only one cohort is being studied, there is no way to know if findings would be different from other cohorts. In addition, changes that are found as individuals age over time could be due to age or to time of measurement effects. That is, the participants are tested at different periods in history, so the variables of age and time of measurement could be confounded (mixed up). For example, what if there is a major shift in workplace training and education between 2020 and 2040, and many of the participants experience a lot more formal education in adulthood, which positively impacts their intelligence scores in 2040? Researchers wouldn’t know if the intelligence scores increased due to growing older or due to a more educated workforce over time between measurements.

Sequential Research Design

Sequential research  designs include elements of both longitudinal and cross-sectional research designs. Similar to longitudinal designs, sequential research features participants who are followed over time; similar to cross-sectional designs, sequential research includes participants of different ages. This research design is also distinct from those that have been discussed previously in that individuals of different ages are enrolled into a study at various points in time to examine age-related changes, development within the same individuals as they age, and to account for the possibility of cohort and/or time of measurement effects

Consider, once again, our example of intelligence and aging. In a study with a sequential design, a researcher might recruit three separate groups of participants (Groups A, B, and C). Group A would be recruited when they are 20 years old in 2010 and would be tested again when they are 50 and 80 years old in 2040 and 2070, respectively (similar in design to the longitudinal study described previously). Group B would be recruited when they are 20 years old in 2040 and would be tested again when they are 50 years old in 2070. Group C would be recruited when they are 20 years old in 2070, and so on.

Figure 7. Example of sequential research design

Studies with sequential designs are powerful because they allow for both longitudinal and cross-sectional comparisons—changes and/or stability with age over time can be measured and compared with differences between age and cohort groups. This research design also allows for the examination of cohort and time of measurement effects. For example, the researcher could examine the intelligence scores of 20-year-olds at different times in history and different cohorts (follow the yellow diagonal lines in figure 3). This might be examined by researchers who are interested in sociocultural and historical changes (because we know that lifespan development is multidisciplinary). One way of looking at the usefulness of the various developmental research designs was described by Schaie and Baltes (1975): cross-sectional and longitudinal designs might reveal change patterns while sequential designs might identify developmental origins for the observed change patterns.

Since they include elements of longitudinal and cross-sectional designs, sequential research has many of the same strengths and limitations as these other approaches. For example, sequential work may require less time and effort than longitudinal research (if data are collected more frequently than over the 30-year spans in our example) but more time and effort than cross-sectional research. Although practice effects may be an issue if participants are asked to complete the same tasks or assessments over time, attrition may be less problematic than what is commonly experienced in longitudinal research since participants may not have to remain involved in the study for such a long period of time.

Comparing Developmental Research Designs

When considering the best research design to use in their research, scientists think about their main research question and the best way to come up with an answer. A table of advantages and disadvantages for each of the described research designs is provided here to help you as you consider what sorts of studies would be best conducted using each of these different approaches.

Table 1.  Advantages and disadvantages of different research designs

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