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Identifying a research problem: a step-by-step guide.

Identifying a research problem is a crucial first step in the research process, serving as the foundation for all subsequent research activities. This guide provides a comprehensive overview of the steps involved in identifying a research problem, from understanding its essence to employing advanced strategies for refinement.

Key Takeaways

Understanding the definition and importance of a research problem is essential for academic success.
Exploring diverse sources such as literature reviews and consultations can help in formulating a solid research problem.
A clear problem statement, aligned research objectives, and well-defined questions are crucial for a focused study.
Evaluating the feasibility and potential impact of a research problem ensures its relevance and scope.
Advanced strategies, including interdisciplinary approaches and technology utilization, can enhance the identification and refinement of research problems.

Understanding the Essence of Identifying a Research Problem

Defining the research problem.

A research problem is the focal point of any academic inquiry. It is a concise and well-defined statement that outlines the specific issue or question that the research aims to address. This research problem usually sets the tone for the entire study and provides you, the researcher, with a clear purpose and a clear direction on how to go about conducting your research.

Importance in Academic Research

It also demonstrates the significance of your research and its potential to contribute new knowledge to the existing body of literature in the world. A compelling research problem not only captivates the attention of your peers but also lays the foundation for impactful and meaningful research outcomes.

Initial Steps to Identification

To identify a research problem, you need a systematic approach and a deep understanding of the subject area. Below are some steps to guide you in this process:

Conduct a thorough literature review to understand what has been studied before.
Identify gaps in the existing research that could form the basis of your study.
Consult with academic mentors to refine your ideas and approach.

Exploring Sources for Research Problem Identification

Literature review.

When you embark on the journey of identifying a research problem, a thorough literature review is indispensable. This process involves scrutinizing existing research to find literature gaps and unexplored areas that could form the basis of your research. It's crucial to analyze recent studies, seminal works, and review articles to ensure a comprehensive understanding of the topic.

Existing Theories and Frameworks

The exploration of existing theories and frameworks provides a solid foundation for developing a research problem. By understanding the established models and theories, you can identify inconsistencies or areas lacking in depth which might offer fruitful avenues for research.

Consultation with Academic Mentors

Engaging with academic mentors is vital in shaping a well-defined research problem. Their expertise can guide you through the complexities of your field, offering insights into feasible research questions and helping you refine your focus. This interaction often leads to the identification of unique and significant research opportunities that align with current academic and industry trends.

Formulating the Research Problem

Crafting a clear problem statement.

To effectively address your research problem, start by crafting a clear problem statement . This involves succinctly describing who is affected by the problem, why it is important, and how your research will contribute to solving it. Ensure your problem statement is concise and specific to guide the entire research process.

Setting Research Objectives

Setting clear research objectives is crucial for maintaining focus throughout your study. These objectives should directly align with the problem statement and guide your research activities. Consider using a bulleted list to outline your main objectives:

Understand the underlying factors contributing to the problem
Explore potential solutions
Evaluate the effectiveness of proposed solutions

Determining Research Questions

The formulation of precise research questions is a pivotal step in defining the scope and direction of your study. These questions should be directly derived from your research objectives and designed to be answerable through your chosen research methods. Crafting well-defined research questions will help you maintain a clear focus and avoid common pitfalls in the research process.

Evaluating the Scope and Relevance of the Research Problem

Feasibility assessment.

Before you finalize a research problem, it is crucial to assess its feasibility. Consider the availability of resources, time, and expertise required to conduct the research. Evaluate potential constraints and determine if the research problem can be realistically tackled within the given limitations.

Significance to the Field

Ensure that your research problem has a clear and direct impact on the field. It should aim to contribute to existing knowledge and address a real-world issue that is relevant to your academic discipline.

Potential Impact on Existing Knowledge

The potential impact of your research problem on existing knowledge cannot be understated. It should challenge, extend, or refine current understanding in a meaningful way. Consider how your research can add value to the existing body of work and potentially lead to significant advancements in your field.

Techniques for Refining the Research Problem

Narrowing down the focus.

To effectively refine your research problem, start by narrowing down the focus . This involves pinpointing the specific aspects of your topic that are most significant and ensuring that your research problem is not too broad. This targeted approach helps in identifying knowledge gaps and formulating more precise research questions.

Incorporating Feedback

Feedback is crucial in the refinement process. Engage with academic mentors, peers, and experts in your field to gather insights and suggestions. This collaborative feedback can lead to significant improvements in your research problem, making it more robust and relevant.

Iterative Refinement Process

Refinement should be seen as an iterative process, where you continuously refine and revise your research problem based on new information and feedback. This approach ensures that your research problem remains aligned with current trends and academic standards, ultimately enhancing its feasibility and relevance.

Challenges in Identifying a Research Problem

Common pitfalls and how to avoid them.

Identifying a research problem can be fraught with common pitfalls such as selecting a topic that is too broad or too narrow. To avoid these, you should conduct a thorough literature review and seek feedback from peers and mentors. This proactive approach ensures that your research question is both relevant and manageable.

Dealing with Ambiguity

Ambiguity in defining the research problem can lead to significant challenges down the line. Ensure clarity by operationalizing variables and explicitly stating the research objectives. This clarity will guide your entire research process, making it more structured and focused.

Balancing Novelty and Practicality

While it's important to address a novel issue in your research, practicality should not be overlooked. A research problem should not only contribute new knowledge but also be feasible and have clear implications. Balancing these aspects often requires iterative refinement and consultation with academic mentors to align your research with real-world applications.

Advanced Strategies for Identifying a Research Problem

Interdisciplinary approaches.

Embrace the power of interdisciplinary approaches to uncover unique and comprehensive research problems. By integrating knowledge from various disciplines, you can address complex issues that single-field studies might overlook. This method not only broadens the scope of your research but also enhances its applicability and depth.

Utilizing Technology and Data Analytics

Leverage technology and data analytics to refine and identify research problems with precision. Advanced tools like machine learning and big data analysis can reveal patterns and insights that traditional methods might miss. This approach is particularly useful in fields where large datasets are involved, or where real-time data integration can lead to more dynamic research outcomes.

Engaging with Industry and Community Needs

Focus on the needs of industry and community to ensure your research is not only academically sound but also practically relevant. Engaging with real-world problems can provide a rich source of research questions that are directly applicable and beneficial to society. This strategy not only enhances the relevance of your research but also increases its potential for impact.

Dive into the world of academic success with our 'Advanced Strategies for Identifying a Research Problem' at Research Rebels. Our expertly crafted guides and action plans are designed to simplify your thesis journey, transforming complex academic challenges into manageable tasks. Don't wait to take control of your academic future. Visit our website now to learn more and claim your special offer!

In conclusion, identifying a research problem is a foundational step in the academic research process that requires careful consideration and systematic approach. This guide has outlined the essential steps involved, from understanding the context and reviewing existing literature to formulating clear research questions. By adhering to these guidelines, researchers can ensure that their studies are grounded in a well-defined problem, enhancing the relevance and impact of their findings. It is crucial for scholars to approach this task with rigor and critical thinking to contribute meaningfully to the body of knowledge in their respective fields.

Frequently Asked Questions

What is a research problem.

A research problem is a specific issue, inconsistency, or gap in knowledge that needs to be addressed through scientific inquiry. It forms the foundation of a research study, guiding the research questions, methodology, and analysis.

Why is identifying a research problem important?

Identifying a research problem is crucial as it determines the direction and scope of the study. It helps researchers focus their inquiry, formulate hypotheses, and contribute to the existing body of knowledge.

How do I identify a suitable research problem?

To identify a suitable research problem, start with a thorough literature review to understand existing research and identify gaps. Consult with academic mentors, and consider relevance, feasibility, and your own interests.

What are some common pitfalls in identifying a research problem?

Common pitfalls include choosing a problem that is too broad or too narrow, not aligning with existing literature, lack of originality, and failing to consider the practical implications and feasibility of the study.

Can technology help in identifying a research problem?

Yes, technology and data analytics can aid in identifying research problems by providing access to a vast amount of data, revealing patterns and trends that might not be visible otherwise. Tools like digital libraries and research databases are particularly useful.

How can I refine my research problem?

Refine your research problem by narrowing its focus, seeking feedback from peers and mentors, and continually reviewing and adjusting the problem statement based on new information and insights gained during preliminary research.

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A research problem is a definite or clear expression [statement] about an area of concern, a condition to be improved upon, a difficulty to be eliminated, or a troubling question that exists in scholarly literature, in theory, or within existing practice that points to a need for meaningful understanding and deliberate investigation. A research problem does not state how to do something, offer a vague or broad proposition, or present a value question. In the social and behavioral sciences, studies are most often framed around examining a problem that needs to be understood and resolved in order to improve society and the human condition.

Bryman, Alan. “The Research Question in Social Research: What is its Role?” International Journal of Social Research Methodology 10 (2007): 5-20; Guba, Egon G., and Yvonna S. Lincoln. “Competing Paradigms in Qualitative Research.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, editors. (Thousand Oaks, CA: Sage, 1994), pp. 105-117; Pardede, Parlindungan. “Identifying and Formulating the Research Problem." Research in ELT: Module 4 (October 2018): 1-13; Li, Yanmei, and Sumei Zhang. "Identifying the Research Problem." In Applied Research Methods in Urban and Regional Planning . (Cham, Switzerland: Springer International Publishing, 2022), pp. 13-21.

Importance of...

The purpose of a problem statement is to:

Introduce the reader to the importance of the topic being studied . The reader is oriented to the significance of the study.
Anchors the research questions, hypotheses, or assumptions to follow . It offers a concise statement about the purpose of your paper.
Place the topic into a particular context that defines the parameters of what is to be investigated.
Provide the framework for reporting the results and indicates what is probably necessary to conduct the study and explain how the findings will present this information.

In the social sciences, the research problem establishes the means by which you must answer the "So What?" question. This declarative question refers to a research problem surviving the relevancy test [the quality of a measurement procedure that provides repeatability and accuracy]. Note that answering the "So What?" question requires a commitment on your part to not only show that you have reviewed the literature, but that you have thoroughly considered the significance of the research problem and its implications applied to creating new knowledge and understanding or informing practice.

To survive the "So What" question, problem statements should possess the following attributes:

Clarity and precision [a well-written statement does not make sweeping generalizations and irresponsible pronouncements; it also does include unspecific determinates like "very" or "giant"],
Demonstrate a researchable topic or issue [i.e., feasibility of conducting the study is based upon access to information that can be effectively acquired, gathered, interpreted, synthesized, and understood],
Identification of what would be studied, while avoiding the use of value-laden words and terms,
Identification of an overarching question or small set of questions accompanied by key factors or variables,
Identification of key concepts and terms,
Articulation of the study's conceptual boundaries or parameters or limitations,
Some generalizability in regards to applicability and bringing results into general use,
Conveyance of the study's importance, benefits, and justification [i.e., regardless of the type of research, it is important to demonstrate that the research is not trivial],
Does not have unnecessary jargon or overly complex sentence constructions; and,
Conveyance of more than the mere gathering of descriptive data providing only a snapshot of the issue or phenomenon under investigation.

Bryman, Alan. “The Research Question in Social Research: What is its Role?” International Journal of Social Research Methodology 10 (2007): 5-20; Brown, Perry J., Allen Dyer, and Ross S. Whaley. "Recreation Research—So What?" Journal of Leisure Research 5 (1973): 16-24; Castellanos, Susie. Critical Writing and Thinking. The Writing Center. Dean of the College. Brown University; Ellis, Timothy J. and Yair Levy Nova. "Framework of Problem-Based Research: A Guide for Novice Researchers on the Development of a Research-Worthy Problem." Informing Science: the International Journal of an Emerging Transdiscipline 11 (2008); Thesis and Purpose Statements. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Thesis Statements. The Writing Center. University of North Carolina; Tips and Examples for Writing Thesis Statements. The Writing Lab and The OWL. Purdue University; Selwyn, Neil. "‘So What?’…A Question that Every Journal Article Needs to Answer." Learning, Media, and Technology 39 (2014): 1-5; Shoket, Mohd. "Research Problem: Identification and Formulation." International Journal of Research 1 (May 2014): 512-518.

Structure and Writing Style

I. Types and Content

There are four general conceptualizations of a research problem in the social sciences:

Casuist Research Problem -- this type of problem relates to the determination of right and wrong in questions of conduct or conscience by analyzing moral dilemmas through the application of general rules and the careful distinction of special cases.
Difference Research Problem -- typically asks the question, “Is there a difference between two or more groups or treatments?” This type of problem statement is used when the researcher compares or contrasts two or more phenomena. This a common approach to defining a problem in the clinical social sciences or behavioral sciences.
Descriptive Research Problem -- typically asks the question, "what is...?" with the underlying purpose to describe the significance of a situation, state, or existence of a specific phenomenon. This problem is often associated with revealing hidden or understudied issues.
Relational Research Problem -- suggests a relationship of some sort between two or more variables to be investigated. The underlying purpose is to investigate specific qualities or characteristics that may be connected in some way.

A problem statement in the social sciences should contain :

A lead-in that helps ensure the reader will maintain interest over the study,
A declaration of originality [e.g., mentioning a knowledge void or a lack of clarity about a topic that will be revealed in the literature review of prior research],
An indication of the central focus of the study [establishing the boundaries of analysis], and
An explanation of the study's significance or the benefits to be derived from investigating the research problem.

NOTE: A statement describing the research problem of your paper should not be viewed as a thesis statement that you may be familiar with from high school. Given the content listed above, a description of the research problem is usually a short paragraph in length.

II. Sources of Problems for Investigation

The identification of a problem to study can be challenging, not because there's a lack of issues that could be investigated, but due to the challenge of formulating an academically relevant and researchable problem which is unique and does not simply duplicate the work of others. To facilitate how you might select a problem from which to build a research study, consider these sources of inspiration:

Deductions from Theory This relates to deductions made from social philosophy or generalizations embodied in life and in society that the researcher is familiar with. These deductions from human behavior are then placed within an empirical frame of reference through research. From a theory, the researcher can formulate a research problem or hypothesis stating the expected findings in certain empirical situations. The research asks the question: “What relationship between variables will be observed if theory aptly summarizes the state of affairs?” One can then design and carry out a systematic investigation to assess whether empirical data confirm or reject the hypothesis, and hence, the theory.

Interdisciplinary Perspectives Identifying a problem that forms the basis for a research study can come from academic movements and scholarship originating in disciplines outside of your primary area of study. This can be an intellectually stimulating exercise. A review of pertinent literature should include examining research from related disciplines that can reveal new avenues of exploration and analysis. An interdisciplinary approach to selecting a research problem offers an opportunity to construct a more comprehensive understanding of a very complex issue that any single discipline may be able to provide.

Interviewing Practitioners The identification of research problems about particular topics can arise from formal interviews or informal discussions with practitioners who provide insight into new directions for future research and how to make research findings more relevant to practice. Discussions with experts in the field, such as, teachers, social workers, health care providers, lawyers, business leaders, etc., offers the chance to identify practical, “real world” problems that may be understudied or ignored within academic circles. This approach also provides some practical knowledge which may help in the process of designing and conducting your study.

Personal Experience Don't undervalue your everyday experiences or encounters as worthwhile problems for investigation. Think critically about your own experiences and/or frustrations with an issue facing society or related to your community, your neighborhood, your family, or your personal life. This can be derived, for example, from deliberate observations of certain relationships for which there is no clear explanation or witnessing an event that appears harmful to a person or group or that is out of the ordinary.

Relevant Literature The selection of a research problem can be derived from a thorough review of pertinent research associated with your overall area of interest. This may reveal where gaps exist in understanding a topic or where an issue has been understudied. Research may be conducted to: 1) fill such gaps in knowledge; 2) evaluate if the methodologies employed in prior studies can be adapted to solve other problems; or, 3) determine if a similar study could be conducted in a different subject area or applied in a different context or to different study sample [i.e., different setting or different group of people]. Also, authors frequently conclude their studies by noting implications for further research; read the conclusion of pertinent studies because statements about further research can be a valuable source for identifying new problems to investigate. The fact that a researcher has identified a topic worthy of further exploration validates the fact it is worth pursuing.

III. What Makes a Good Research Statement?

A good problem statement begins by introducing the broad area in which your research is centered, gradually leading the reader to the more specific issues you are investigating. The statement need not be lengthy, but a good research problem should incorporate the following features:

1. Compelling Topic The problem chosen should be one that motivates you to address it but simple curiosity is not a good enough reason to pursue a research study because this does not indicate significance. The problem that you choose to explore must be important to you, but it must also be viewed as important by your readers and to a the larger academic and/or social community that could be impacted by the results of your study. 2. Supports Multiple Perspectives The problem must be phrased in a way that avoids dichotomies and instead supports the generation and exploration of multiple perspectives. A general rule of thumb in the social sciences is that a good research problem is one that would generate a variety of viewpoints from a composite audience made up of reasonable people. 3. Researchability This isn't a real word but it represents an important aspect of creating a good research statement. It seems a bit obvious, but you don't want to find yourself in the midst of investigating a complex research project and realize that you don't have enough prior research to draw from for your analysis. There's nothing inherently wrong with original research, but you must choose research problems that can be supported, in some way, by the resources available to you. If you are not sure if something is researchable, don't assume that it isn't if you don't find information right away--seek help from a librarian !

NOTE: Do not confuse a research problem with a research topic. A topic is something to read and obtain information about, whereas a problem is something to be solved or framed as a question raised for inquiry, consideration, or solution, or explained as a source of perplexity, distress, or vexation. In short, a research topic is something to be understood; a research problem is something that needs to be investigated.

IV. Asking Analytical Questions about the Research Problem

Research problems in the social and behavioral sciences are often analyzed around critical questions that must be investigated. These questions can be explicitly listed in the introduction [i.e., "This study addresses three research questions about women's psychological recovery from domestic abuse in multi-generational home settings..."], or, the questions are implied in the text as specific areas of study related to the research problem. Explicitly listing your research questions at the end of your introduction can help in designing a clear roadmap of what you plan to address in your study, whereas, implicitly integrating them into the text of the introduction allows you to create a more compelling narrative around the key issues under investigation. Either approach is appropriate.

The number of questions you attempt to address should be based on the complexity of the problem you are investigating and what areas of inquiry you find most critical to study. Practical considerations, such as, the length of the paper you are writing or the availability of resources to analyze the issue can also factor in how many questions to ask. In general, however, there should be no more than four research questions underpinning a single research problem.

Given this, well-developed analytical questions can focus on any of the following:

Highlights a genuine dilemma, area of ambiguity, or point of confusion about a topic open to interpretation by your readers;
Yields an answer that is unexpected and not obvious rather than inevitable and self-evident;
Provokes meaningful thought or discussion;
Raises the visibility of the key ideas or concepts that may be understudied or hidden;
Suggests the need for complex analysis or argument rather than a basic description or summary; and,
Offers a specific path of inquiry that avoids eliciting generalizations about the problem.

NOTE: Questions of how and why concerning a research problem often require more analysis than questions about who, what, where, and when. You should still ask yourself these latter questions, however. Thinking introspectively about the who, what, where, and when of a research problem can help ensure that you have thoroughly considered all aspects of the problem under investigation and helps define the scope of the study in relation to the problem.

V. Mistakes to Avoid

Beware of circular reasoning! Do not state the research problem as simply the absence of the thing you are suggesting. For example, if you propose the following, "The problem in this community is that there is no hospital," this only leads to a research problem where:

The need is for a hospital
The objective is to create a hospital
The method is to plan for building a hospital, and
The evaluation is to measure if there is a hospital or not.

This is an example of a research problem that fails the "So What?" test . In this example, the problem does not reveal the relevance of why you are investigating the fact there is no hospital in the community [e.g., perhaps there's a hospital in the community ten miles away]; it does not elucidate the significance of why one should study the fact there is no hospital in the community [e.g., that hospital in the community ten miles away has no emergency room]; the research problem does not offer an intellectual pathway towards adding new knowledge or clarifying prior knowledge [e.g., the county in which there is no hospital already conducted a study about the need for a hospital, but it was conducted ten years ago]; and, the problem does not offer meaningful outcomes that lead to recommendations that can be generalized for other situations or that could suggest areas for further research [e.g., the challenges of building a new hospital serves as a case study for other communities].

Alvesson, Mats and Jörgen Sandberg. “Generating Research Questions Through Problematization.” Academy of Management Review 36 (April 2011): 247-271 ; Choosing and Refining Topics. Writing@CSU. Colorado State University; D'Souza, Victor S. "Use of Induction and Deduction in Research in Social Sciences: An Illustration." Journal of the Indian Law Institute 24 (1982): 655-661; Ellis, Timothy J. and Yair Levy Nova. "Framework of Problem-Based Research: A Guide for Novice Researchers on the Development of a Research-Worthy Problem." Informing Science: the International Journal of an Emerging Transdiscipline 11 (2008); How to Write a Research Question. The Writing Center. George Mason University; Invention: Developing a Thesis Statement. The Reading/Writing Center. Hunter College; Problem Statements PowerPoint Presentation. The Writing Lab and The OWL. Purdue University; Procter, Margaret. Using Thesis Statements. University College Writing Centre. University of Toronto; Shoket, Mohd. "Research Problem: Identification and Formulation." International Journal of Research 1 (May 2014): 512-518; Trochim, William M.K. Problem Formulation. Research Methods Knowledge Base. 2006; Thesis and Purpose Statements. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Thesis Statements. The Writing Center. University of North Carolina; Tips and Examples for Writing Thesis Statements. The Writing Lab and The OWL. Purdue University; Pardede, Parlindungan. “Identifying and Formulating the Research Problem." Research in ELT: Module 4 (October 2018): 1-13; Walk, Kerry. Asking an Analytical Question. [Class handout or worksheet]. Princeton University; White, Patrick. Developing Research Questions: A Guide for Social Scientists . New York: Palgrave McMillan, 2009; Li, Yanmei, and Sumei Zhang. "Identifying the Research Problem." In Applied Research Methods in Urban and Regional Planning . (Cham, Switzerland: Springer International Publishing, 2022), pp. 13-21.

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Home » Research Problem – Examples, Types and Guide

Research Problem – Examples, Types and Guide

Table of Contents

Research Problem

Definition:

Research problem is a specific and well-defined issue or question that a researcher seeks to investigate through research. It is the starting point of any research project, as it sets the direction, scope, and purpose of the study.

Types of Research Problems

Types of Research Problems are as follows:

Descriptive problems

These problems involve describing or documenting a particular phenomenon, event, or situation. For example, a researcher might investigate the demographics of a particular population, such as their age, gender, income, and education.

Exploratory problems

These problems are designed to explore a particular topic or issue in depth, often with the goal of generating new ideas or hypotheses. For example, a researcher might explore the factors that contribute to job satisfaction among employees in a particular industry.

Explanatory Problems

These problems seek to explain why a particular phenomenon or event occurs, and they typically involve testing hypotheses or theories. For example, a researcher might investigate the relationship between exercise and mental health, with the goal of determining whether exercise has a causal effect on mental health.

Predictive Problems

These problems involve making predictions or forecasts about future events or trends. For example, a researcher might investigate the factors that predict future success in a particular field or industry.

Evaluative Problems

These problems involve assessing the effectiveness of a particular intervention, program, or policy. For example, a researcher might evaluate the impact of a new teaching method on student learning outcomes.

How to Define a Research Problem

Defining a research problem involves identifying a specific question or issue that a researcher seeks to address through a research study. Here are the steps to follow when defining a research problem:

Identify a broad research topic : Start by identifying a broad topic that you are interested in researching. This could be based on your personal interests, observations, or gaps in the existing literature.
Conduct a literature review : Once you have identified a broad topic, conduct a thorough literature review to identify the current state of knowledge in the field. This will help you identify gaps or inconsistencies in the existing research that can be addressed through your study.
Refine the research question: Based on the gaps or inconsistencies identified in the literature review, refine your research question to a specific, clear, and well-defined problem statement. Your research question should be feasible, relevant, and important to the field of study.
Develop a hypothesis: Based on the research question, develop a hypothesis that states the expected relationship between variables.
Define the scope and limitations: Clearly define the scope and limitations of your research problem. This will help you focus your study and ensure that your research objectives are achievable.
Get feedback: Get feedback from your advisor or colleagues to ensure that your research problem is clear, feasible, and relevant to the field of study.

Components of a Research Problem

The components of a research problem typically include the following:

Topic : The general subject or area of interest that the research will explore.
Research Question : A clear and specific question that the research seeks to answer or investigate.
Objective : A statement that describes the purpose of the research, what it aims to achieve, and the expected outcomes.
Hypothesis : An educated guess or prediction about the relationship between variables, which is tested during the research.
Variables : The factors or elements that are being studied, measured, or manipulated in the research.
Methodology : The overall approach and methods that will be used to conduct the research.
Scope and Limitations : A description of the boundaries and parameters of the research, including what will be included and excluded, and any potential constraints or limitations.
Significance: A statement that explains the potential value or impact of the research, its contribution to the field of study, and how it will add to the existing knowledge.

Research Problem Examples

Following are some Research Problem Examples:

Research Problem Examples in Psychology are as follows:

Exploring the impact of social media on adolescent mental health.
Investigating the effectiveness of cognitive-behavioral therapy for treating anxiety disorders.
Studying the impact of prenatal stress on child development outcomes.
Analyzing the factors that contribute to addiction and relapse in substance abuse treatment.
Examining the impact of personality traits on romantic relationships.

Research Problem Examples in Sociology are as follows:

Investigating the relationship between social support and mental health outcomes in marginalized communities.
Studying the impact of globalization on labor markets and employment opportunities.
Analyzing the causes and consequences of gentrification in urban neighborhoods.
Investigating the impact of family structure on social mobility and economic outcomes.
Examining the effects of social capital on community development and resilience.

Research Problem Examples in Economics are as follows:

Studying the effects of trade policies on economic growth and development.
Analyzing the impact of automation and artificial intelligence on labor markets and employment opportunities.
Investigating the factors that contribute to economic inequality and poverty.
Examining the impact of fiscal and monetary policies on inflation and economic stability.
Studying the relationship between education and economic outcomes, such as income and employment.

Political Science

Research Problem Examples in Political Science are as follows:

Analyzing the causes and consequences of political polarization and partisan behavior.
Investigating the impact of social movements on political change and policymaking.
Studying the role of media and communication in shaping public opinion and political discourse.
Examining the effectiveness of electoral systems in promoting democratic governance and representation.
Investigating the impact of international organizations and agreements on global governance and security.

Environmental Science

Research Problem Examples in Environmental Science are as follows:

Studying the impact of air pollution on human health and well-being.
Investigating the effects of deforestation on climate change and biodiversity loss.
Analyzing the impact of ocean acidification on marine ecosystems and food webs.
Studying the relationship between urban development and ecological resilience.
Examining the effectiveness of environmental policies and regulations in promoting sustainability and conservation.

Research Problem Examples in Education are as follows:

Investigating the impact of teacher training and professional development on student learning outcomes.
Studying the effectiveness of technology-enhanced learning in promoting student engagement and achievement.
Analyzing the factors that contribute to achievement gaps and educational inequality.
Examining the impact of parental involvement on student motivation and achievement.
Studying the effectiveness of alternative educational models, such as homeschooling and online learning.

Research Problem Examples in History are as follows:

Analyzing the social and economic factors that contributed to the rise and fall of ancient civilizations.
Investigating the impact of colonialism on indigenous societies and cultures.
Studying the role of religion in shaping political and social movements throughout history.
Analyzing the impact of the Industrial Revolution on economic and social structures.
Examining the causes and consequences of global conflicts, such as World War I and II.

Research Problem Examples in Business are as follows:

Studying the impact of corporate social responsibility on brand reputation and consumer behavior.
Investigating the effectiveness of leadership development programs in improving organizational performance and employee satisfaction.
Analyzing the factors that contribute to successful entrepreneurship and small business development.
Examining the impact of mergers and acquisitions on market competition and consumer welfare.
Studying the effectiveness of marketing strategies and advertising campaigns in promoting brand awareness and sales.

Research Problem Example for Students

An Example of a Research Problem for Students could be:

“How does social media usage affect the academic performance of high school students?”

This research problem is specific, measurable, and relevant. It is specific because it focuses on a particular area of interest, which is the impact of social media on academic performance. It is measurable because the researcher can collect data on social media usage and academic performance to evaluate the relationship between the two variables. It is relevant because it addresses a current and important issue that affects high school students.

To conduct research on this problem, the researcher could use various methods, such as surveys, interviews, and statistical analysis of academic records. The results of the study could provide insights into the relationship between social media usage and academic performance, which could help educators and parents develop effective strategies for managing social media use among students.

Another example of a research problem for students:

“Does participation in extracurricular activities impact the academic performance of middle school students?”

This research problem is also specific, measurable, and relevant. It is specific because it focuses on a particular type of activity, extracurricular activities, and its impact on academic performance. It is measurable because the researcher can collect data on students’ participation in extracurricular activities and their academic performance to evaluate the relationship between the two variables. It is relevant because extracurricular activities are an essential part of the middle school experience, and their impact on academic performance is a topic of interest to educators and parents.

To conduct research on this problem, the researcher could use surveys, interviews, and academic records analysis. The results of the study could provide insights into the relationship between extracurricular activities and academic performance, which could help educators and parents make informed decisions about the types of activities that are most beneficial for middle school students.

Applications of Research Problem

Applications of Research Problem are as follows:

Academic research: Research problems are used to guide academic research in various fields, including social sciences, natural sciences, humanities, and engineering. Researchers use research problems to identify gaps in knowledge, address theoretical or practical problems, and explore new areas of study.
Business research : Research problems are used to guide business research, including market research, consumer behavior research, and organizational research. Researchers use research problems to identify business challenges, explore opportunities, and develop strategies for business growth and success.
Healthcare research : Research problems are used to guide healthcare research, including medical research, clinical research, and health services research. Researchers use research problems to identify healthcare challenges, develop new treatments and interventions, and improve healthcare delivery and outcomes.
Public policy research : Research problems are used to guide public policy research, including policy analysis, program evaluation, and policy development. Researchers use research problems to identify social issues, assess the effectiveness of existing policies and programs, and develop new policies and programs to address societal challenges.
Environmental research : Research problems are used to guide environmental research, including environmental science, ecology, and environmental management. Researchers use research problems to identify environmental challenges, assess the impact of human activities on the environment, and develop sustainable solutions to protect the environment.

Purpose of Research Problems

The purpose of research problems is to identify an area of study that requires further investigation and to formulate a clear, concise and specific research question. A research problem defines the specific issue or problem that needs to be addressed and serves as the foundation for the research project.

Identifying a research problem is important because it helps to establish the direction of the research and sets the stage for the research design, methods, and analysis. It also ensures that the research is relevant and contributes to the existing body of knowledge in the field.

A well-formulated research problem should:

Clearly define the specific issue or problem that needs to be investigated
Be specific and narrow enough to be manageable in terms of time, resources, and scope
Be relevant to the field of study and contribute to the existing body of knowledge
Be feasible and realistic in terms of available data, resources, and research methods
Be interesting and intellectually stimulating for the researcher and potential readers or audiences.

Characteristics of Research Problem

The characteristics of a research problem refer to the specific features that a problem must possess to qualify as a suitable research topic. Some of the key characteristics of a research problem are:

Clarity : A research problem should be clearly defined and stated in a way that it is easily understood by the researcher and other readers. The problem should be specific, unambiguous, and easy to comprehend.
Relevance : A research problem should be relevant to the field of study, and it should contribute to the existing body of knowledge. The problem should address a gap in knowledge, a theoretical or practical problem, or a real-world issue that requires further investigation.
Feasibility : A research problem should be feasible in terms of the availability of data, resources, and research methods. It should be realistic and practical to conduct the study within the available time, budget, and resources.
Novelty : A research problem should be novel or original in some way. It should represent a new or innovative perspective on an existing problem, or it should explore a new area of study or apply an existing theory to a new context.
Importance : A research problem should be important or significant in terms of its potential impact on the field or society. It should have the potential to produce new knowledge, advance existing theories, or address a pressing societal issue.
Manageability : A research problem should be manageable in terms of its scope and complexity. It should be specific enough to be investigated within the available time and resources, and it should be broad enough to provide meaningful results.

Advantages of Research Problem

The advantages of a well-defined research problem are as follows:

Focus : A research problem provides a clear and focused direction for the research study. It ensures that the study stays on track and does not deviate from the research question.
Clarity : A research problem provides clarity and specificity to the research question. It ensures that the research is not too broad or too narrow and that the research objectives are clearly defined.
Relevance : A research problem ensures that the research study is relevant to the field of study and contributes to the existing body of knowledge. It addresses gaps in knowledge, theoretical or practical problems, or real-world issues that require further investigation.
Feasibility : A research problem ensures that the research study is feasible in terms of the availability of data, resources, and research methods. It ensures that the research is realistic and practical to conduct within the available time, budget, and resources.
Novelty : A research problem ensures that the research study is original and innovative. It represents a new or unique perspective on an existing problem, explores a new area of study, or applies an existing theory to a new context.
Importance : A research problem ensures that the research study is important and significant in terms of its potential impact on the field or society. It has the potential to produce new knowledge, advance existing theories, or address a pressing societal issue.
Rigor : A research problem ensures that the research study is rigorous and follows established research methods and practices. It ensures that the research is conducted in a systematic, objective, and unbiased manner.

About the author

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Research Problem – Definition, Steps & Tips

Published by Jamie Walker at August 12th, 2021 , Revised On October 3, 2023

Once you have chosen a research topic, the next stage is to explain the research problem: the detailed issue, ambiguity of the research, gap analysis, or gaps in knowledge and findings that you will discuss.

Here, in this article, we explore a research problem in a dissertation or an essay with some research problem examples to help you better understand how and when you should write a research problem.

“A research problem is a specific statement relating to an area of concern and is contingent on the type of research. Some research studies focus on theoretical and practical problems, while some focus on only one.”

The problem statement in the dissertation, essay, research paper, and other academic papers should be clearly stated and intended to expand information, knowledge, and contribution to change.

This article will assist in identifying and elaborating a research problem if you are unsure how to define your research problem. The most notable challenge in the research process is to formulate and identify a research problem. Formulating a problem statement and research questions while finalizing the research proposal or introduction for your dissertation or thesis is necessary.

Why is Research Problem Critical?

An interesting research topic is only the first step. The real challenge of the research process is to develop a well-rounded research problem.

A well-formulated research problem helps understand the research procedure; without it, your research will appear unforeseeable and awkward.

Research is a procedure based on a sequence and a research problem aids in following and completing the research in a sequence. Repetition of existing literature is something that should be avoided in research.

Therefore research problem in a dissertation or an essay needs to be well thought out and presented with a clear purpose. Hence, your research work contributes more value to existing knowledge. You need to be well aware of the problem so you can present logical solutions.

Formulating a research problem is the first step of conducting research, whether you are writing an essay, research paper, dissertation , or research proposal .

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Step 1: Identifying Problem Area – What is Research Problem

The most significant step in any research is to look for unexplored areas, topics, and controversies . You aim to find gaps that your work will fill. Here are some research problem examples for you to better understand the concept.

Practical Research Problems

To conduct practical research, you will need practical research problems that are typically identified by analysing reports, previous research studies, and interactions with the experienced personals of pertinent disciplines. You might search for:

Problems with performance or competence in an organization
Institutional practices that could be enhanced
Practitioners of relevant fields and their areas of concern
Problems confronted by specific groups of people within your area of study

If your research work relates to an internship or a job, then it will be critical for you to identify a research problem that addresses certain issues faced by the firm the job or internship pertains to.

Examples of Practical Research Problems

Decreased voter participation in county A, as compared to the rest of the country.

The high employee turnover rate of department X of company Y influenced efficiency and team performance.

A charity institution, Y, suffers a lack of funding resulting in budget cuts for its programmes.

Theoretical Research Problems

Theoretical research relates to predicting, explaining, and understanding various phenomena. It also expands and challenges existing information and knowledge.

Identification of a research problem in theoretical research is achieved by analysing theories and fresh research literature relating to a broad area of research. This practice helps to find gaps in the research done by others and endorse the argument of your topic.

Here are some questions that you should bear in mind.

A case or framework that has not been deeply analysed
An ambiguity between more than one viewpoints
An unstudied condition or relationships
A problematic issue that needs to be addressed

Theoretical issues often contain practical implications, but immediate issues are often not resolved by these results. If that is the case, you might want to adopt a different research approach to achieve the desired outcomes.

Examples of Theoretical Research Problems

Long-term Vitamin D deficiency affects cardiac patients are not well researched.

The relationship between races, sex, and income imbalances needs to be studied with reference to the economy of a specific country or region.

The disagreement among historians of Scottish nationalism regarding the contributions of Imperial Britain in the creation of the national identity for Scotland.

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Step 2: Understanding the Research Problem

The researcher further investigates the selected area of research to find knowledge and information relating to the research problem to address the findings in the research.

Background and Rationale

Population influenced by the problem?
Is it a persistent problem, or is it recently revealed?
Research that has already been conducted on this problem?
Any proposed solution to the problem?
Recent arguments concerning the problem, what are the gaps in the problem?

How to Write a First Class Dissertation Proposal or Research Proposal

Particularity and Suitability

What specific place, time, and/or people will be focused on?
Any aspects of research that you may not be able to deal with?
What will be the concerns if the problem remains unresolved?
What are the benefices of the problem resolution (e.g. future researcher or organisation’s management)?

Example of a Specific Research Problem

A non-profit institution X has been examined on their existing support base retention, but the existing research does not incorporate an understanding of how to effectively target new donors. To continue their work, the institution needs more research and find strategies for effective fundraising.

Once the problem is narrowed down, the next stage is to propose a problem statement and hypothesis or research questions.

If you are unsure about what a research problem is and how to define the research problem, then you might want to take advantage of our dissertation proposal writing service. You may also want to take a look at our essay writing service if you need help with identifying a research problem for your essay.

Frequently Asked Questions

What is research problem with example.

A research problem is a specific challenge that requires investigation. Example: “What is the impact of social media on mental health among adolescents?” This problem drives research to analyse the relationship between social media use and mental well-being in young people.

How many types of research problems do we have?

Descriptive: Describing phenomena as they exist.
Explanatory: Understanding causes and effects.
Exploratory: Investigating little-understood phenomena.
Predictive: Forecasting future outcomes.
Prescriptive: Recommending actions.
Normative: Describing what ought to be.

What are the principles of the research problem?

Relevance: Addresses a significant issue.
Re searchability: Amenable to empirical investigation.
Clarity: Clearly defined without ambiguity.
Specificity: Narrowly framed, avoiding vagueness.
Feasibility: Realistic to conduct with available resources.
Novelty: Offers new insights or challenges existing knowledge.
Ethical considerations: Respect rights, dignity, and safety.

Why is research problem important?

A research problem is crucial because it identifies knowledge gaps, directs the inquiry’s focus, and forms the foundation for generating hypotheses or questions. It drives the methodology and determination of study relevance, ensuring that research contributes meaningfully to academic discourse and potentially addresses real-world challenges.

How do you write a research problem?

To write a research problem, identify a knowledge gap or an unresolved issue in your field. Start with a broad topic, then narrow it down. Clearly articulate the problem in a concise statement, ensuring it’s researchable, significant, and relevant. Ground it in the existing literature to highlight its importance and context.

How can we solve research problem?

To solve a research problem, start by conducting a thorough literature review. Formulate hypotheses or research questions. Choose an appropriate research methodology. Collect and analyse data systematically. Interpret findings in the context of existing knowledge. Ensure validity and reliability, and discuss implications, limitations, and potential future research directions.

The Importance of a Well-Defined Research Problem.

In the labyrinthine world of academic research, a well-defined research problem serves as the North Star, guiding scholars and scientists on their intellectual voyages of discovery. It is the compass that steers research endeavors toward meaningful, impactful, and enlightening destinations. In this comprehensive blog, we will delve into the paramount significance of a well-defined research problem and explore why it stands as the bedrock of all scholarly pursuits.

The Essence of a Well-Defined Research Problem.

A well-defined research problem is more than just a question; it is a gateway to understanding, a key to unlocking the mysteries of the universe, and a catalyst for innovation. Here’s why it is so crucial:

1. Precision and Focus.

A research problem carves a path through the dense forest of potential research areas. It provides clarity and precision, helping researchers channel their efforts effectively. Without a well-defined problem, research can drift aimlessly, leading to inconclusive results or even dead ends.

2. Relevance and Significance.

An effective research problem doesn’t exist in a vacuum; it addresses real-world issues and concerns. It tackles questions or challenges that are pertinent to a specific field or even society at large. This relevance is what makes research meaningful and impactful.

3. Structured Research.

Think of a research problem as the blueprint for your research journey. It dictates the structure and organization of your study, determining what literature to review, which methodologies to employ, and how data should be analyzed. Without this foundation, research can become disjointed and chaotic.

4. Knowledge Advancement.

At its core, research aims to expand the boundaries of human knowledge. A well-defined problem encapsulates the gap in existing knowledge, highlighting precisely what needs to be explored or understood. This, in turn, propels the collective intellect forward.

5. Practical Application.

Many research problems have direct implications for practical applications. Whether it’s developing new medical treatments, optimizing renewable energy sources, or improving educational techniques, research problems lay the groundwork for solutions that can benefit society.

Formulating a Well-Defined Research Problem.

Creating a well-defined research problem is both an art and a science. It requires a thoughtful and systematic approach:

1. Choose Your Field.

Begin by selecting the academic field or domain you are passionate about. Your research problem should align with your interests and expertise.

2. Extensive Literature Review.

A thorough literature review is paramount. It helps you understand what has already been explored, what questions remain unanswered, and where the gaps in knowledge lie.

3. Identify the Gap.

Based on your literature review, pinpoint the specific gap or issue you want to investigate. Your research problem should be a concise, focused statement that encapsulates this gap.

4. Set Clear Objectives.

Define the objectives or goals of your research. What do you intend to achieve by addressing this problem? What are the expected outcomes?

5. Scope and Feasibility.

Determine the scope of your research and assess its feasibility. Ensure that your research problem can be tackled within the constraints of time, resources, and ethical considerations.

6. Seek Feedback.

Don’t hesitate to consult with mentors, peers, or experts in your field. Their input can help refine and validate your research problem.

The Ripple Effect of Well-Defined Research Problems.

A well-defined research problem has a far-reaching impact that extends beyond the confines of academia:

1. Scientific Progress.

Research problems are the driving force behind scientific advancements. They encourage researchers to push boundaries, challenge established theories, and pioneer new paradigms.

2. Technological Innovation.

Many of the technological marvels that shape our world today emerged from research endeavors aimed at solving specific problems. From the internet to medical breakthroughs, research problems drive innovation.

3. Societal Transformation.

Research that addresses pressing social, economic, or environmental issues can catalyze profound societal transformations. It can inform policies, drive advocacy, and empower communities.

4. Intellectual Growth.

Engaging with research problems fosters intellectual growth. It nurtures critical thinking, problem-solving skills, and a deeper understanding of the world.

Conclusion.

In the grand tapestry of human knowledge, a well-defined research problem is the warp and weft that weave together insights, discoveries, and innovations. It is the crucible in which curiosity transforms into wisdom, and the spark that ignites the fires of progress. Whether you are a researcher embarking on a new project or a curious mind seeking to understand the world, always remember that a well-defined research problem is your compass, your guide, and your ticket to the frontiers of knowledge.

How to identify and resolve research problems

Updated July 12, 2023

In this article, we’re going to take you through one of the most pertinent parts of conducting research: a research problem (also known as a research problem statement).

When trying to formulate a good research statement, and understand how to solve it for complex projects, it can be difficult to know where to start.

Not only are there multiple perspectives (from stakeholders to project marketers who want answers), you have to consider the particular context of the research topic: is it timely, is it relevant and most importantly of all, is it valuable?

In other words: are you looking at a research worthy problem?

The fact is, a well-defined, precise, and goal-centric research problem will keep your researchers, stakeholders, and business-focused and your results actionable.

And when it works well, it's a powerful tool to identify practical solutions that can drive change and secure buy-in from your workforce.

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What is a research problem?

In social research methodology and behavioral sciences , a research problem establishes the direction of research, often relating to a specific topic or opportunity for discussion.

For example: climate change and sustainability, analyzing moral dilemmas or wage disparity amongst classes could all be areas that the research problem focuses on.

As well as outlining the topic and/or opportunity, a research problem will explain:

why the area/issue needs to be addressed,
why the area/issue is of importance,
the parameters of the research study
the research objective
the reporting framework for the results and
what the overall benefit of doing so will provide (whether to society as a whole or other researchers and projects).

Having identified the main topic or opportunity for discussion, you can then narrow it down into one or several specific questions that can be scrutinized and answered through the research process.

What are research questions?

Generating research questions underpinning your study usually starts with problems that require further research and understanding while fulfilling the objectives of the study.

A good problem statement begins by asking deeper questions to gain insights about a specific topic.

For example, using the problems above, our questions could be:

"How will climate change policies influence sustainability standards across specific geographies?"

"What measures can be taken to address wage disparity without increasing inflation?"

Developing a research worthy problem is the first step - and one of the most important - in any kind of research.

It’s also a task that will come up again and again because any business research process is cyclical. New questions arise as you iterate and progress through discovering, refining, and improving your products and processes. A research question can also be referred to as a "problem statement".

Note: good research supports multiple perspectives through empirical data. It’s focused on key concepts rather than a broad area, providing readily actionable insight and areas for further research.

Research question or research problem?

As we've highlighted, the terms “research question” and “research problem” are often used interchangeably, becoming a vague or broad proposition for many.

The term "problem statement" is far more representative, but finds little use among academics.

Instead, some researchers think in terms of a single research problem and several research questions that arise from it.

As mentioned above, the questions are lines of inquiry to explore in trying to solve the overarching research problem.

Ultimately, this provides a more meaningful understanding of a topic area.

It may be useful to think of questions and problems as coming out of your business data – that’s the O-data (otherwise known as operational data) like sales figures and website metrics.

What's an example of a research problem?

Your overall research problem could be: "How do we improve sales across EMEA and reduce lost deals?"

This research problem then has a subset of questions, such as:

"Why do sales peak at certain times of the day?"

"Why are customers abandoning their online carts at the point of sale?"

As well as helping you to solve business problems, research problems (and associated questions) help you to think critically about topics and/or issues (business or otherwise). You can also use your old research to aid future research -- a good example is laying the foundation for comparative trend reports or a complex research project.

(Also, if you want to see the bigger picture when it comes to research problems, why not check out our ultimate guide to market research? In it you'll find out: what effective market research looks like, the use cases for market research, carrying out a research study, and how to examine and action research findings).

The research process: why are research problems important?

A research problem has two essential roles in setting your research project on a course for success.

1. They set the scope

The research problem defines what problem or opportunity you’re looking at and what your research goals are. It stops you from getting side-tracked or allowing the scope of research to creep off-course .

Without a strong research problem or problem statement, your team could end up spending resources unnecessarily, or coming up with results that aren’t actionable - or worse, harmful to your business - because the field of study is too broad.

2. They tie your work to business goals and actions

To formulate a research problem in terms of business decisions means you always have clarity on what’s needed to make those decisions. You can show the effects of what you’ve studied using real outcomes.

Then, by focusing your research problem statement on a series of questions tied to business objectives, you can reduce the risk of the research being unactionable or inaccurate.

It's also worth examining research or other scholarly literature (you’ll find plenty of similar, pertinent research online) to see how others have explored specific topics and noting implications that could have for your research.

Four steps to defining your research problem

Image credit: http://myfreeschooltanzania.blogspot.com/2014/11/defining-research-problem.html

1. Observe and identify

Businesses today have so much data that it can be difficult to know which problems to address first. Researchers also have business stakeholders who come to them with problems they would like to have explored. A researcher’s job is to sift through these inputs and discover exactly what higher-level trends and key concepts are worth investing in.

This often means asking questions and doing some initial investigation to decide which avenues to pursue. This could mean gathering interdisciplinary perspectives identifying additional expertise and contextual information.

Sometimes, a small-scale preliminary study might be worth doing to help get a more comprehensive understanding of the business context and needs, and to make sure your research problem addresses the most critical questions.

This could take the form of qualitative research using a few in-depth interviews , an environmental scan, or reviewing relevant literature.

The sales manager of a sportswear company has a problem: sales of trail running shoes are down year-on-year and she isn’t sure why. She approaches the company’s research team for input and they begin asking questions within the company and reviewing their knowledge of the wider market.

2. Review the key factors involved

As a marketing researcher, you must work closely with your team of researchers to define and test the influencing factors and the wider context involved in your study. These might include demographic and economic trends or the business environment affecting the question at hand. This is referred to as a relational research problem.

To do this, you have to identify the factors that will affect the research and begin formulating different methods to control them.

You also need to consider the relationships between factors and the degree of control you have over them. For example, you may be able to control the loading speed of your website but you can’t control the fluctuations of the stock market.

Doing this will help you determine whether the findings of your project will produce enough information to be worth the cost.

You need to determine:

which factors affect the solution to the research proposal.
which ones can be controlled and used for the purposes of the company, and to what extent.
the functional relationships between the factors.
which ones are critical to the solution of the research study.

The research team at the running shoe company is hard at work. They explore the factors involved and the context of why YoY sales are down for trail shoes, including things like what the company’s competitors are doing, what the weather has been like – affecting outdoor exercise – and the relative spend on marketing for the brand from year to year.

The final factor is within the company’s control, although the first two are not. They check the figures and determine marketing spend has a significant impact on the company.

3. Prioritize

Once you and your research team have a few observations, prioritize them based on their business impact and importance. It may be that you can answer more than one question with a single study, but don’t do it at the risk of losing focus on your overarching research problem.

Questions to ask:

Who? Who are the people with the problem? Are they end-users, stakeholders, teams within your business? Have you validated the information to see what the scale of the problem is?
What? What is its nature and what is the supporting evidence?
Why? What is the business case for solving the problem? How will it help?
Where? How does the problem manifest and where is it observed?

To help you understand all dimensions, you might want to consider focus groups or preliminary interviews with external (including consumers and existing customers) and internal (salespeople, managers, and other stakeholders) parties to provide what is sometimes much-needed insight into a particular set of questions or problems.

After observing and investigating, the running shoe researchers come up with a few candidate questions, including:

What is the relationship between US average temperatures and sales of our products year on year?
At present, how does our customer base rank Competitor X and Competitor Y’s trail running shoe compared to our brand?
What is the relationship between marketing spend and trail shoe product sales over the last 12 months?

They opt for the final question, because the variables involved are fully within the company’s control, and based on their initial research and stakeholder input, seem the most likely cause of the dive in sales. The research question is specific enough to keep the work on course towards an actionable result, but it allows for a few different avenues to be explored, such as the different budget allocations of offline and online marketing and the kinds of messaging used.

Get feedback from the key teams within your business to make sure everyone is aligned and has the same understanding of the research problem and questions, and the actions you hope to take based on the results. Now is also a good time to demonstrate the ROI of your research and lay out its potential benefits to your stakeholders.

Different groups may have different goals and perspectives on the issue. This step is vital for getting the necessary buy-in and pushing the project forward.

The running shoe company researchers now have everything they need to begin. They call a meeting with the sales manager and consult with the product team, marketing team, and C-suite to make sure everyone is aligned and has bought into the direction of the research topic. They identify and agree that the likely course of action will be a rethink of how marketing resources are allocated, and potentially testing out some new channels and messaging strategies .

Can you explore a broad area and is it practical to do so?

A broader research problem or report can be a great way to bring attention to prevalent issues, societal or otherwise, but are often undertaken by those with the resources to do so.

Take a typical government cybersecurity breach survey, for example. Most of these reports raise awareness of cybercrime, from the day-to-day threats businesses face to what security measures some organizations are taking. What these reports don't do, however, is provide actionable advice - mostly because every organization is different.

The point here is that while some researchers will explore a very complex issue in detail, others will provide only a snapshot to maintain interest and encourage further investigation. The "value" of the data is wholly determined by the recipients of it - and what information you choose to include.

To summarize, it can be practical to undertake a broader research problem, certainly, but it may not be possible to cover everything or provide the detail your audience needs. Likewise, a more systematic investigation of an issue or topic will be more valuable, but you may also find that you cover far less ground.

It's important to think about your research objectives and expected findings before going ahead.

Ensuring your research project is a success

A complex research project can be made significantly easier with clear research objectives, a descriptive research problem, and a central focus. All of which we've outlined in this article.

If you have previous research, even better. Use it as a benchmark

Remember: what separates a good research paper from an average one is actually very simple: valuable, empirical data that explores a prevalent societal or business issue and provides actionable insights.

And we can help.

Sophisticated research made simple with Qualtrics

Trusted by the world's best brands, our platform enables researchers from academic to corporate to tackle the hardest challenges and deliver the results that matter.

Our CoreXM platform supports the methods that define superior research and delivers insights in real-time. It's easy to use (thanks to drag-and-drop functionality) and requires no coding, meaning you'll be capturing data and gleaning insights in no time.

It also excels in flexibility; you can track consumer behavior across segments , benchmark your company versus competitors , carry out complex academic research, and do much more, all from one system.

It's one platform with endless applications, so no matter your research problem, we've got the tools to help you solve it. And if you don't have a team of research experts in-house, our market research team has the practical knowledge and tools to help design the surveys and find the respondents you need.

Of course, you may want to know where to begin with your own market research . If you're struggling, make sure to download our ultimate guide using the link below.

It's got everything you need and there’s always information in our research methods knowledge base.

Scott Smith

Scott Smith, Ph.D. is a contributor to the Qualtrics blog.

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Defining a Research Problem

Defining a research problem is the fuel that drives the scientific process, and is the foundation of any research method and experimental design, from true experiment to case study.

This article is a part of the guide:

Null Hypothesis
Research Hypothesis
Selecting Method
Test Hypothesis

Browse Full Outline

1 Scientific Method
2.1.1 Null Hypothesis
2.1.2 Research Hypothesis
2.2 Prediction
2.3 Conceptual Variable
3.1 Operationalization
3.2 Selecting Method
3.3 Measurements
3.4 Scientific Observation
4.1 Empirical Evidence
5.1 Generalization
5.2 Errors in Conclusion

It is one of the first statements made in any research paper and, as well as defining the research area, should include a quick synopsis of how the hypothesis was arrived at.

Operationalization is then used to give some indication of the exact definitions of the variables, and the type of scientific measurements used.

This will lead to the proposal of a viable hypothesis . As an aside, when scientists are putting forward proposals for research funds, the quality of their research problem often makes the difference between success and failure.

Structuring the Research Problem

Look at any scientific paper, and you will see the research problem, written almost like a statement of intent.

Defining a research problem is crucial in defining the quality of the answers, and determines the exact research method used. A quantitative experimental design uses deductive reasoning to arrive at a testable hypothesis .

Qualitative research designs use inductive reasoning to propose a research statement.

Formulating the research problem begins during the first steps of the scientific process .

As an example, a literature review and a study of previous experiments, and research, might throw up some vague areas of interest.

Many scientific researchers look at an area where a previous researcher generated some interesting results, but never followed up. It could be an interesting area of research, which nobody else has fully explored.

A scientist may even review a successful experiment, disagree with the results , the tests used, or the methodology , and decide to refine the research process, retesting the hypothesis .

This is called the conceptual definition, and is an overall view of the problem. A science report will generally begin with an overview of the previous research and real-world observations. The researcher will then state how this led to defining a research problem.

The Operational Definitions

The operational definition is the determining the scalar properties of the variables .

For example, temperature, weight and time are usually well known and defined, with only the exact scale used needing definition. If a researcher is measuring abstract concepts, such as intelligence, emotions, and subjective responses, then a system of measuring numerically needs to be established, allowing statistical analysis and replication.

For example, intelligence may be measured with IQ and human responses could be measured with a questionnaire from ‘1- strongly disagree’, to ‘5 - strongly agree’.

Behavioral biologists and social scientists might design an ordinal scale for measuring and rating behavior. These measurements are always subjective, but allow statistics and replication of the whole research method. This is all an essential part of defining a research problem.

Examples of Defining a Research Problem

An anthropologist might find references to a relatively unknown tribe in Papua New Guinea. Through inductive reasoning , she arrives at the research problem and asks,

‘How do these people live and how does their culture relate to nearby tribes?’

She has found a gap in knowledge, and she seeks to fill it, using a qualitative case study , without a hypothesis.

The Bandura Bobo Doll Experiment is a good example of using deductive reasoning to arrive at a research problem and hypothesis.

Anecdotal evidence showed that violent behavior amongst children was increasing. Bandura believed that higher levels of violent adult role models on television, was a contributor to this rise. This was expanded into a hypothesis , and operationalization of the variables, and scientific measurement scale , led to a robust experimental design.

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Martyn Shuttleworth (Oct 2, 2008). Defining a Research Problem. Retrieved Jun 01, 2024 from Explorable.com: https://explorable.com/defining-a-research-problem

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2.1 Why Is Research Important?

Learning objectives.

By the end of this section, you will be able to:

Explain how scientific research addresses questions about behavior
Discuss how scientific research guides public policy
Appreciate how scientific research can be important in making personal decisions

Scientific research is a critical tool for successfully navigating our complex world. Without it, we would be forced to rely solely on intuition, other people’s authority, and blind luck. While many of us feel confident in our abilities to decipher and interact with the world around us, history is filled with examples of how very wrong we can be when we fail to recognize the need for evidence in supporting claims. At various times in history, we would have been certain that the sun revolved around a flat earth, that the earth’s continents did not move, and that mental illness was caused by possession ( Figure 2.2 ). It is through systematic scientific research that we divest ourselves of our preconceived notions and superstitions and gain an objective understanding of ourselves and our world.

The goal of all scientists is to better understand the world around them. Psychologists focus their attention on understanding behavior, as well as the cognitive (mental) and physiological (body) processes that underlie behavior. In contrast to other methods that people use to understand the behavior of others, such as intuition and personal experience, the hallmark of scientific research is that there is evidence to support a claim. Scientific knowledge is empirical : It is grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing.

While behavior is observable, the mind is not. If someone is crying, we can see behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes we can learn the reason for someone’s behavior by simply asking a question, like “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This chapter explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

Use of Research Information

Trying to determine which theories are and are not accepted by the scientific community can be difficult, especially in an area of research as broad as psychology. More than ever before, we have an incredible amount of information at our fingertips, and a simple internet search on any given research topic might result in a number of contradictory studies. In these cases, we are witnessing the scientific community going through the process of reaching a consensus, and it could be quite some time before a consensus emerges. For example, the explosion in our use of technology has led researchers to question whether this ultimately helps or hinders us. The use and implementation of technology in educational settings has become widespread over the last few decades. Researchers are coming to different conclusions regarding the use of technology. To illustrate this point, a study investigating a smartphone app targeting surgery residents (graduate students in surgery training) found that the use of this app can increase student engagement and raise test scores (Shaw & Tan, 2015). Conversely, another study found that the use of technology in undergraduate student populations had negative impacts on sleep, communication, and time management skills (Massimini & Peterson, 2009). Until sufficient amounts of research have been conducted, there will be no clear consensus on the effects that technology has on a student's acquisition of knowledge, study skills, and mental health.

In the meantime, we should strive to think critically about the information we encounter by exercising a degree of healthy skepticism. When someone makes a claim, we should examine the claim from a number of different perspectives: what is the expertise of the person making the claim, what might they gain if the claim is valid, does the claim seem justified given the evidence, and what do other researchers think of the claim? This is especially important when we consider how much information in advertising campaigns and on the internet claims to be based on “scientific evidence” when in actuality it is a belief or perspective of just a few individuals trying to sell a product or draw attention to their perspectives.

We should be informed consumers of the information made available to us because decisions based on this information have significant consequences. One such consequence can be seen in politics and public policy. Imagine that you have been elected as the governor of your state. One of your responsibilities is to manage the state budget and determine how to best spend your constituents’ tax dollars. As the new governor, you need to decide whether to continue funding early intervention programs. These programs are designed to help children who come from low-income backgrounds, have special needs, or face other disadvantages. These programs may involve providing a wide variety of services to maximize the children's development and position them for optimal levels of success in school and later in life (Blann, 2005). While such programs sound appealing, you would want to be sure that they also proved effective before investing additional money in these programs. Fortunately, psychologists and other scientists have conducted vast amounts of research on such programs and, in general, the programs are found to be effective (Neil & Christensen, 2009; Peters-Scheffer, Didden, Korzilius, & Sturmey, 2011). While not all programs are equally effective, and the short-term effects of many such programs are more pronounced, there is reason to believe that many of these programs produce long-term benefits for participants (Barnett, 2011). If you are committed to being a good steward of taxpayer money, you would want to look at research. Which programs are most effective? What characteristics of these programs make them effective? Which programs promote the best outcomes? After examining the research, you would be best equipped to make decisions about which programs to fund.

Link to Learning

Watch this video about early childhood program effectiveness to learn how scientists evaluate effectiveness and how best to invest money into programs that are most effective.

Ultimately, it is not just politicians who can benefit from using research in guiding their decisions. We all might look to research from time to time when making decisions in our lives. Imagine that your sister, Maria, expresses concern about her two-year-old child, Umberto. Umberto does not speak as much or as clearly as the other children in his daycare or others in the family. Umberto's pediatrician undertakes some screening and recommends an evaluation by a speech pathologist, but does not refer Maria to any other specialists. Maria is concerned that Umberto's speech delays are signs of a developmental disorder, but Umberto's pediatrician does not; she sees indications of differences in Umberto's jaw and facial muscles. Hearing this, you do some internet searches, but you are overwhelmed by the breadth of information and the wide array of sources. You see blog posts, top-ten lists, advertisements from healthcare providers, and recommendations from several advocacy organizations. Why are there so many sites? Which are based in research, and which are not?

In the end, research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.

NOTABLE RESEARCHERS

Psychological research has a long history involving important figures from diverse backgrounds. While the introductory chapter discussed several researchers who made significant contributions to the discipline, there are many more individuals who deserve attention in considering how psychology has advanced as a science through their work ( Figure 2.3 ). For instance, Margaret Floy Washburn (1871–1939) was the first woman to earn a PhD in psychology. Her research focused on animal behavior and cognition (Margaret Floy Washburn, PhD, n.d.). Mary Whiton Calkins (1863–1930) was a preeminent first-generation American psychologist who opposed the behaviorist movement, conducted significant research into memory, and established one of the earliest experimental psychology labs in the United States (Mary Whiton Calkins, n.d.).

Francis Sumner (1895–1954) was the first African American to receive a PhD in psychology in 1920. His dissertation focused on issues related to psychoanalysis. Sumner also had research interests in racial bias and educational justice. Sumner was one of the founders of Howard University’s department of psychology, and because of his accomplishments, he is sometimes referred to as the “Father of Black Psychology.” Thirteen years later, Inez Beverly Prosser (1895–1934) became the first African American woman to receive a PhD in psychology. Prosser’s research highlighted issues related to education in segregated versus integrated schools, and ultimately, her work was very influential in the hallmark Brown v. Board of Education Supreme Court ruling that segregation of public schools was unconstitutional (Ethnicity and Health in America Series: Featured Psychologists, n.d.).

Although the establishment of psychology’s scientific roots occurred first in Europe and the United States, it did not take much time until researchers from around the world began to establish their own laboratories and research programs. For example, some of the first experimental psychology laboratories in South America were founded by Horatio Piñero (1869–1919) at two institutions in Buenos Aires, Argentina (Godoy & Brussino, 2010). In India, Gunamudian David Boaz (1908–1965) and Narendra Nath Sen Gupta (1889–1944) established the first independent departments of psychology at the University of Madras and the University of Calcutta, respectively. These developments provided an opportunity for Indian researchers to make important contributions to the field (Gunamudian David Boaz, n.d.; Narendra Nath Sen Gupta, n.d.).

When the American Psychological Association (APA) was first founded in 1892, all of the members were White males (Women and Minorities in Psychology, n.d.). However, by 1905, Mary Whiton Calkins was elected as the first female president of the APA, and by 1946, nearly one-quarter of American psychologists were female. Psychology became a popular degree option for students enrolled in the nation’s historically Black higher education institutions, increasing the number of Black Americans who went on to become psychologists. Given demographic shifts occurring in the United States and increased access to higher educational opportunities among historically underrepresented populations, there is reason to hope that the diversity of the field will increasingly match the larger population, and that the research contributions made by the psychologists of the future will better serve people of all backgrounds (Women and Minorities in Psychology, n.d.).

The Process of Scientific Research

Scientific knowledge is advanced through a process known as the scientific method . Basically, ideas (in the form of theories and hypotheses) are tested against the real world (in the form of empirical observations), and those empirical observations lead to more ideas that are tested against the real world, and so on. In this sense, the scientific process is circular. The types of reasoning within the circle are called deductive and inductive. In deductive reasoning , ideas are tested in the real world; in inductive reasoning , real-world observations lead to new ideas ( Figure 2.4 ). These processes are inseparable, like inhaling and exhaling, but different research approaches place different emphasis on the deductive and inductive aspects.

In the scientific context, deductive reasoning begins with a generalization—one hypothesis—that is then used to reach logical conclusions about the real world. If the hypothesis is correct, then the logical conclusions reached through deductive reasoning should also be correct. A deductive reasoning argument might go something like this: All living things require energy to survive (this would be your hypothesis). Ducks are living things. Therefore, ducks require energy to survive (logical conclusion). In this example, the hypothesis is correct; therefore, the conclusion is correct as well. Sometimes, however, an incorrect hypothesis may lead to a logical but incorrect conclusion. Consider this argument: all ducks are born with the ability to see. Quackers is a duck. Therefore, Quackers was born with the ability to see. Scientists use deductive reasoning to empirically test their hypotheses. Returning to the example of the ducks, researchers might design a study to test the hypothesis that if all living things require energy to survive, then ducks will be found to require energy to survive.

Deductive reasoning starts with a generalization that is tested against real-world observations; however, inductive reasoning moves in the opposite direction. Inductive reasoning uses empirical observations to construct broad generalizations. Unlike deductive reasoning, conclusions drawn from inductive reasoning may or may not be correct, regardless of the observations on which they are based. For instance, you may notice that your favorite fruits—apples, bananas, and oranges—all grow on trees; therefore, you assume that all fruit must grow on trees. This would be an example of inductive reasoning, and, clearly, the existence of strawberries, blueberries, and kiwi demonstrate that this generalization is not correct despite it being based on a number of direct observations. Scientists use inductive reasoning to formulate theories, which in turn generate hypotheses that are tested with deductive reasoning. In the end, science involves both deductive and inductive processes.

For example, case studies, which you will read about in the next section, are heavily weighted on the side of empirical observations. Thus, case studies are closely associated with inductive processes as researchers gather massive amounts of observations and seek interesting patterns (new ideas) in the data. Experimental research, on the other hand, puts great emphasis on deductive reasoning.

We’ve stated that theories and hypotheses are ideas, but what sort of ideas are they, exactly? A theory is a well-developed set of ideas that propose an explanation for observed phenomena. Theories are repeatedly checked against the world, but they tend to be too complex to be tested all at once; instead, researchers create hypotheses to test specific aspects of a theory.

A hypothesis is a testable prediction about how the world will behave if our idea is correct, and it is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests Figure 2.5 .

To see how this process works, let’s consider a specific theory and a hypothesis that might be generated from that theory. As you’ll learn in a later chapter, the James-Lange theory of emotion asserts that emotional experience relies on the physiological arousal associated with the emotional state. If you walked out of your home and discovered a very aggressive snake waiting on your doorstep, your heart would begin to race and your stomach churn. According to the James-Lange theory, these physiological changes would result in your feeling of fear. A hypothesis that could be derived from this theory might be that a person who is unaware of the physiological arousal that the sight of the snake elicits will not feel fear.

A scientific hypothesis is also falsifiable , or capable of being shown to be incorrect. Recall from the introductory chapter that Sigmund Freud had lots of interesting ideas to explain various human behaviors ( Figure 2.6 ). However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable; for example, it is impossible to imagine empirical observations that would disprove the existence of the id, the ego, and the superego—the three elements of personality described in Freud’s theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

In contrast, the James-Lange theory does generate falsifiable hypotheses, such as the one described above. Some individuals who suffer significant injuries to their spinal columns are unable to feel the bodily changes that often accompany emotional experiences. Therefore, we could test the hypothesis by determining how emotional experiences differ between individuals who have the ability to detect these changes in their physiological arousal and those who do not. In fact, this research has been conducted and while the emotional experiences of people deprived of an awareness of their physiological arousal may be less intense, they still experience emotion (Chwalisz, Diener, & Gallagher, 1988).

Scientific research’s dependence on falsifiability allows for great confidence in the information that it produces. Typically, by the time information is accepted by the scientific community, it has been tested repeatedly.

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Home / Why the research question is so important

Why the research question is so important

04/05/2018 at 5:42 am

A research question is a sentence that defines what you will examine, within which population, and what the outcome of interest will be. Defining a clear research question is the first and most important part of the project. Though it sounds simple, writing a research question is tricky even for experienced researchers. This video will build your understanding of where to start looking for research questions, how to write them, and why it is important to work with a solid research question from the beginning of the project.

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Links to useful research papers.

Farrugia P, Petrisor BA, Farrokhyar F, Bhandari M. Research questions, hypotheses and objectives. Canadian Journal of Surgery. 2010;53(4):278-281. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2912019/

Aslam, S., & Emmanuel, P. (2010). Formulating a researchable question: A critical step for facilitating good clinical research. Indian J Sex Transm Dis, 31(1), 47-50. https://www.ncbi.nlm.nih.gov/pubmed/21808439

Beitz, J. M. (2006). Writing the researchable question. J Wound Ostomy Continence Nurs, 33(2), 122-124. https://www.ncbi.nlm.nih.gov/pubmed/16572009

Links to useful websites

Centre for Clinical Effectivenbess

http://www.monashhealth.org/page/Resources

Centre for Evidence Based Medicine

https://www.cebm.net/category/ebm-resources/tools/

Libraries in SWSLHD

https://www.swslhd.health.nsw.gov.au/liverpool/library/default.html

https://www.swslhd.health.nsw.gov.au/ccq/library/

https://www.swslhd.health.nsw.gov.au/Fairfield/library/

https://www.swslhd.health.nsw.gov.au/bankstown/library/

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Case Study Research Method in Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Case studies are in-depth investigations of a person, group, event, or community. Typically, data is gathered from various sources using several methods (e.g., observations & interviews).

The case study research method originated in clinical medicine (the case history, i.e., the patient’s personal history). In psychology, case studies are often confined to the study of a particular individual.

The information is mainly biographical and relates to events in the individual’s past (i.e., retrospective), as well as to significant events that are currently occurring in his or her everyday life.

The case study is not a research method, but researchers select methods of data collection and analysis that will generate material suitable for case studies.

Freud (1909a, 1909b) conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

This makes it clear that the case study is a method that should only be used by a psychologist, therapist, or psychiatrist, i.e., someone with a professional qualification.

There is an ethical issue of competence. Only someone qualified to diagnose and treat a person can conduct a formal case study relating to atypical (i.e., abnormal) behavior or atypical development.

Famous Case Studies

Anna O – One of the most famous case studies, documenting psychoanalyst Josef Breuer’s treatment of “Anna O” (real name Bertha Pappenheim) for hysteria in the late 1800s using early psychoanalytic theory.
Little Hans – A child psychoanalysis case study published by Sigmund Freud in 1909 analyzing his five-year-old patient Herbert Graf’s house phobia as related to the Oedipus complex.
Bruce/Brenda – Gender identity case of the boy (Bruce) whose botched circumcision led psychologist John Money to advise gender reassignment and raise him as a girl (Brenda) in the 1960s.
Genie Wiley – Linguistics/psychological development case of the victim of extreme isolation abuse who was studied in 1970s California for effects of early language deprivation on acquiring speech later in life.
Phineas Gage – One of the most famous neuropsychology case studies analyzes personality changes in railroad worker Phineas Gage after an 1848 brain injury involving a tamping iron piercing his skull.

Clinical Case Studies

Studying the effectiveness of psychotherapy approaches with an individual patient
Assessing and treating mental illnesses like depression, anxiety disorders, PTSD
Neuropsychological cases investigating brain injuries or disorders

Child Psychology Case Studies

Studying psychological development from birth through adolescence
Cases of learning disabilities, autism spectrum disorders, ADHD
Effects of trauma, abuse, deprivation on development

Types of Case Studies

Explanatory case studies : Used to explore causation in order to find underlying principles. Helpful for doing qualitative analysis to explain presumed causal links.
Exploratory case studies : Used to explore situations where an intervention being evaluated has no clear set of outcomes. It helps define questions and hypotheses for future research.
Descriptive case studies : Describe an intervention or phenomenon and the real-life context in which it occurred. It is helpful for illustrating certain topics within an evaluation.
Multiple-case studies : Used to explore differences between cases and replicate findings across cases. Helpful for comparing and contrasting specific cases.
Intrinsic : Used to gain a better understanding of a particular case. Helpful for capturing the complexity of a single case.
Collective : Used to explore a general phenomenon using multiple case studies. Helpful for jointly studying a group of cases in order to inquire into the phenomenon.

Where Do You Find Data for a Case Study?

There are several places to find data for a case study. The key is to gather data from multiple sources to get a complete picture of the case and corroborate facts or findings through triangulation of evidence. Most of this information is likely qualitative (i.e., verbal description rather than measurement), but the psychologist might also collect numerical data.

1. Primary sources

Interviews – Interviewing key people related to the case to get their perspectives and insights. The interview is an extremely effective procedure for obtaining information about an individual, and it may be used to collect comments from the person’s friends, parents, employer, workmates, and others who have a good knowledge of the person, as well as to obtain facts from the person him or herself.
Observations – Observing behaviors, interactions, processes, etc., related to the case as they unfold in real-time.
Documents & Records – Reviewing private documents, diaries, public records, correspondence, meeting minutes, etc., relevant to the case.

2. Secondary sources

News/Media – News coverage of events related to the case study.
Academic articles – Journal articles, dissertations etc. that discuss the case.
Government reports – Official data and records related to the case context.
Books/films – Books, documentaries or films discussing the case.

3. Archival records

Searching historical archives, museum collections and databases to find relevant documents, visual/audio records related to the case history and context.

Public archives like newspapers, organizational records, photographic collections could all include potentially relevant pieces of information to shed light on attitudes, cultural perspectives, common practices and historical contexts related to psychology.

4. Organizational records

Organizational records offer the advantage of often having large datasets collected over time that can reveal or confirm psychological insights.

Of course, privacy and ethical concerns regarding confidential data must be navigated carefully.

However, with proper protocols, organizational records can provide invaluable context and empirical depth to qualitative case studies exploring the intersection of psychology and organizations.

Organizational/industrial psychology research : Organizational records like employee surveys, turnover/retention data, policies, incident reports etc. may provide insight into topics like job satisfaction, workplace culture and dynamics, leadership issues, employee behaviors etc.
Clinical psychology : Therapists/hospitals may grant access to anonymized medical records to study aspects like assessments, diagnoses, treatment plans etc. This could shed light on clinical practices.
School psychology : Studies could utilize anonymized student records like test scores, grades, disciplinary issues, and counseling referrals to study child development, learning barriers, effectiveness of support programs, and more.

How do I Write a Case Study in Psychology?

Follow specified case study guidelines provided by a journal or your psychology tutor. General components of clinical case studies include: background, symptoms, assessments, diagnosis, treatment, and outcomes. Interpreting the information means the researcher decides what to include or leave out. A good case study should always clarify which information is the factual description and which is an inference or the researcher’s opinion.

1. Introduction

Provide background on the case context and why it is of interest, presenting background information like demographics, relevant history, and presenting problem.
Compare briefly to similar published cases if applicable. Clearly state the focus/importance of the case.

2. Case Presentation

Describe the presenting problem in detail, including symptoms, duration,and impact on daily life.
Include client demographics like age and gender, information about social relationships, and mental health history.
Describe all physical, emotional, and/or sensory symptoms reported by the client.
Use patient quotes to describe the initial complaint verbatim. Follow with full-sentence summaries of relevant history details gathered, including key components that led to a working diagnosis.
Summarize clinical exam results, namely orthopedic/neurological tests, imaging, lab tests, etc. Note actual results rather than subjective conclusions. Provide images if clearly reproducible/anonymized.
Clearly state the working diagnosis or clinical impression before transitioning to management.

3. Management and Outcome

Indicate the total duration of care and number of treatments given over what timeframe. Use specific names/descriptions for any therapies/interventions applied.
Present the results of the intervention,including any quantitative or qualitative data collected.
For outcomes, utilize visual analog scales for pain, medication usage logs, etc., if possible. Include patient self-reports of improvement/worsening of symptoms. Note the reason for discharge/end of care.

4. Discussion

Analyze the case, exploring contributing factors, limitations of the study, and connections to existing research.
Analyze the effectiveness of the intervention,considering factors like participant adherence, limitations of the study, and potential alternative explanations for the results.
Identify any questions raised in the case analysis and relate insights to established theories and current research if applicable. Avoid definitive claims about physiological explanations.
Offer clinical implications, and suggest future research directions.

5. Additional Items

Thank specific assistants for writing support only. No patient acknowledgments.
References should directly support any key claims or quotes included.
Use tables/figures/images only if substantially informative. Include permissions and legends/explanatory notes.
Provides detailed (rich qualitative) information.
Provides insight for further research.
Permitting investigation of otherwise impractical (or unethical) situations.

Case studies allow a researcher to investigate a topic in far more detail than might be possible if they were trying to deal with a large number of research participants (nomothetic approach) with the aim of ‘averaging’.

Because of their in-depth, multi-sided approach, case studies often shed light on aspects of human thinking and behavior that would be unethical or impractical to study in other ways.

Research that only looks into the measurable aspects of human behavior is not likely to give us insights into the subjective dimension of experience, which is important to psychoanalytic and humanistic psychologists.

Case studies are often used in exploratory research. They can help us generate new ideas (that might be tested by other methods). They are an important way of illustrating theories and can help show how different aspects of a person’s life are related to each other.

The method is, therefore, important for psychologists who adopt a holistic point of view (i.e., humanistic psychologists ).

Limitations

Lacking scientific rigor and providing little basis for generalization of results to the wider population.
Researchers’ own subjective feelings may influence the case study (researcher bias).
Difficult to replicate.
Time-consuming and expensive.
The volume of data, together with the time restrictions in place, impacted the depth of analysis that was possible within the available resources.

Because a case study deals with only one person/event/group, we can never be sure if the case study investigated is representative of the wider body of “similar” instances. This means the conclusions drawn from a particular case may not be transferable to other settings.

Because case studies are based on the analysis of qualitative (i.e., descriptive) data , a lot depends on the psychologist’s interpretation of the information she has acquired.

This means that there is a lot of scope for Anna O , and it could be that the subjective opinions of the psychologist intrude in the assessment of what the data means.

For example, Freud has been criticized for producing case studies in which the information was sometimes distorted to fit particular behavioral theories (e.g., Little Hans ).

This is also true of Money’s interpretation of the Bruce/Brenda case study (Diamond, 1997) when he ignored evidence that went against his theory.

Breuer, J., & Freud, S. (1895). Studies on hysteria . Standard Edition 2: London.

Curtiss, S. (1981). Genie: The case of a modern wild child .

Diamond, M., & Sigmundson, K. (1997). Sex Reassignment at Birth: Long-term Review and Clinical Implications. Archives of Pediatrics & Adolescent Medicine , 151(3), 298-304

Freud, S. (1909a). Analysis of a phobia of a five year old boy. In The Pelican Freud Library (1977), Vol 8, Case Histories 1, pages 169-306

Freud, S. (1909b). Bemerkungen über einen Fall von Zwangsneurose (Der “Rattenmann”). Jb. psychoanal. psychopathol. Forsch ., I, p. 357-421; GW, VII, p. 379-463; Notes upon a case of obsessional neurosis, SE , 10: 151-318.

Harlow J. M. (1848). Passage of an iron rod through the head. Boston Medical and Surgical Journal, 39 , 389–393.

Harlow, J. M. (1868). Recovery from the Passage of an Iron Bar through the Head . Publications of the Massachusetts Medical Society. 2 (3), 327-347.

Money, J., & Ehrhardt, A. A. (1972). Man & Woman, Boy & Girl : The Differentiation and Dimorphism of Gender Identity from Conception to Maturity. Baltimore, Maryland: Johns Hopkins University Press.

Money, J., & Tucker, P. (1975). Sexual signatures: On being a man or a woman.

Further Information

Case Study Approach
Case Study Method
Enhancing the Quality of Case Studies in Health Services Research
“We do things together” A case study of “couplehood” in dementia
Using mixed methods for evaluating an integrative approach to cancer care: a case study

Research Methodology

Qualitative Data Coding

What Is a Focus Group?

Cross-Cultural Research Methodology In Psychology

What Is Internal Validity In Research?

Research Methodology , Statistics

What Is Face Validity In Research? Importance & How To Measure

Criterion Validity: Definition & Examples

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How to Define a Research Problem | Ideas & Examples

How to Define a Research Problem | Ideas & Examples

Published on 8 November 2022 by Shona McCombes and Tegan George.

A research problem is a specific issue or gap in existing knowledge that you aim to address in your research. You may choose to look for practical problems aimed at contributing to change, or theoretical problems aimed at expanding knowledge.

Some research will do both of these things, but usually the research problem focuses on one or the other. The type of research problem you choose depends on your broad topic of interest and the type of research you think will fit best.

This article helps you identify and refine a research problem. When writing your research proposal or introduction , formulate it as a problem statement and/or research questions .

Why is the research problem important, step 1: identify a broad problem area, step 2: learn more about the problem, frequently asked questions about research problems.

Having an interesting topic isn’t a strong enough basis for academic research. Without a well-defined research problem, you are likely to end up with an unfocused and unmanageable project.

You might end up repeating what other people have already said, trying to say too much, or doing research without a clear purpose and justification. You need a clear problem in order to do research that contributes new and relevant insights.

Whether you’re planning your thesis , starting a research paper , or writing a research proposal , the research problem is the first step towards knowing exactly what you’ll do and why.

Prevent plagiarism, run a free check.

As you read about your topic, look for under-explored aspects or areas of concern, conflict, or controversy. Your goal is to find a gap that your research project can fill.

Practical research problems

If you are doing practical research, you can identify a problem by reading reports, following up on previous research, or talking to people who work in the relevant field or organisation. You might look for:

Issues with performance or efficiency
Processes that could be improved
Areas of concern among practitioners
Difficulties faced by specific groups of people

Examples of practical research problems

Voter turnout in New England has been decreasing, in contrast to the rest of the country.

The HR department of a local chain of restaurants has a high staff turnover rate.

A non-profit organisation faces a funding gap that means some of its programs will have to be cut.

Theoretical research problems

If you are doing theoretical research, you can identify a research problem by reading existing research, theory, and debates on your topic to find a gap in what is currently known about it. You might look for:

A phenomenon or context that has not been closely studied
A contradiction between two or more perspectives
A situation or relationship that is not well understood
A troubling question that has yet to be resolved

Examples of theoretical research problems

The effects of long-term Vitamin D deficiency on cardiovascular health are not well understood.

The relationship between gender, race, and income inequality has yet to be closely studied in the context of the millennial gig economy.

Historians of Scottish nationalism disagree about the role of the British Empire in the development of Scotland’s national identity.

Next, you have to find out what is already known about the problem, and pinpoint the exact aspect that your research will address.

Context and background

Who does the problem affect?
Is it a newly-discovered problem, or a well-established one?
What research has already been done?
What, if any, solutions have been proposed?
What are the current debates about the problem? What is missing from these debates?

Specificity and relevance

What particular place, time, and/or group of people will you focus on?
What aspects will you not be able to tackle?
What will the consequences be if the problem is not resolved?

Example of a specific research problem

A local non-profit organisation focused on alleviating food insecurity has always fundraised from its existing support base. It lacks understanding of how best to target potential new donors. To be able to continue its work, the organisation requires research into more effective fundraising strategies.

Once you have narrowed down your research problem, the next step is to formulate a problem statement , as well as your research questions or hypotheses .

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement.

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .

A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis – a prediction that will be confirmed or disproved by 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 .

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Explaining research performance: investigating the importance of motivation

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Published: 23 May 2024
Volume 4 , article number 105 , ( 2024 )

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Silje Marie Svartefoss ORCID: orcid.org/0000-0001-5072-1293 1 nAff4 ,
Jens Jungblut 2 ,
Dag W. Aksnes 1 ,
Kristoffer Kolltveit 2 &
Thed van Leeuwen 3

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In this article, we study the motivation and performance of researchers. More specifically, we investigate what motivates researchers across different research fields and countries and how this motivation influences their research performance. The basis for our study is a large-N survey of economists, cardiologists, and physicists in Denmark, Norway, Sweden, the Netherlands, and the UK. The analysis shows that researchers are primarily motivated by scientific curiosity and practical application and less so by career considerations. There are limited differences across fields and countries, suggesting that the mix of motivational aspects has a common academic core less influenced by disciplinary standards or different national environments. Linking motivational factors to research performance, through bibliometric data on publication productivity and citation impact, our data show that those driven by practical application aspects of motivation have a higher probability for high productivity. Being driven by career considerations also increases productivity but only to a certain extent before it starts having a detrimental effect.

Theories of Motivation in Education: an Integrative Framework

How to design bibliometric research: an overview and a framework proposal

Scientific Truth in a Post-Truth Era: A Review*

Avoid common mistakes on your manuscript.

Introduction

Motivation and abilities are known to be as important factors in explaining employees’ job performance of employees (Van Iddekinge et al. 2018 ), and in the vast scientific literature on motivation, it is common to differentiate between intrinsic and extrinsic motivation factors (Ryan and Deci 2000 ). In this context, path-breaking individuals are said to often be intrinsically motivated (Jindal-Snape and Snape 2006 ; Thomas and Nedeva 2012 ; Vallerand et al. 1992 ), and it has been found that the importance of these of types of motivations differs across occupations and career stages (Duarte and Lopes 2018 ).

In this article, we address the issue of motivation for one specific occupation, namely: researchers working at universities. Specifically, we investigate what motivates researchers across fields and countries (RQ1) and how this motivation is linked to their research performance (RQ2). The question of why people are motivated to do their jobs is interesting to address in an academic context, where work is usually harder to control, and individuals tend to have a lot of much freedom in structuring their work. Moreover, there have been indications that academics possess an especially high level of motivation for their tasks that is not driven by a search for external rewards but by an intrinsic satisfaction from academic work (Evans and Meyer 2003 ; Leslie 2002 ). At the same time, elements of researchers’ performance are measurable through indicators of their publication activity: their productivity through the number of outputs they produce and the impact of their research through the number of citations their publications receive (Aksnes and Sivertsen 2019 ; Wilsdon et al. 2015 ).

Elevating research performance is high on the agenda of many research organisations (Hazelkorn 2015 ). How such performance may be linked to individuals’ motivational aspects has received little attention. Thus, a better understanding of this interrelation may be relevant for developing institutional strategies to foster environments that promote high-quality research and research productivity.

Previous qualitative research has shown that scientists are mainly intrinsically motivated (Jindal-Snape and Snape 2006 ). Other survey-based contributions suggest that there can be differences in motivations across disciplines (Atta-Owusu and Fitjar 2021 ; Lam 2011 ). Furthermore, the performance of individual scientists has been shown to be highly skewed in terms of publication productivity and citation rates (Larivière et al. 2010 ; Ruiz-Castillo and Costas 2014 ). There is a large body of literature explaining these differences. Some focus on national and institutional funding schemes (Hammarfelt and de Rijcke 2015 ; Melguizo and Strober 2007 ) and others on the research environment, such as the presence of research groups and international collaboration (Jeong et al. 2014 ), while many studies address the role of academic rank, age, and gender (see e.g. Baccini et al. 2014 ; Rørstad and Aksnes 2015 ). Until recently, less emphasis has been placed on the impact of researchers’ motivation. Some studies have found that different types of motivations drive high levels of research performance (see e.g. Horodnic and Zaiţ 2015 ; Ryan and Berbegal-Mirabent 2016 ). However, researchers are only starting to understand how this internal drive relates to research performance.

While some of the prior research on the impact of motivation depends on self-reported research performance evaluations (Ryan 2014 ), the present article combines survey responses with actual bibliometric data. To investigate variation in research motivation across scientific fields and countries, we draw on a large-N survey of economists, cardiologists, and physicists in Denmark, Norway, Sweden, the Netherlands, and the UK. To investigate how this motivation is linked to their research performance, we map the survey respondents’ publication and citation data from the Web of Science (WoS).

This article is organised as follows. First, we present relevant literature on research performance and motivation. Next, the scientific fields and countries are then presented before elaborating on our methodology. In the empirical analysis, we investigate variations in motivation across fields, gender, age, and academic position and then relate motivation to publications and citations as our two measures of research performance. In the concluding section, we discuss our findings and implications for national decision-makers and individual researchers.

Motivation and research performance

As noted above, the concepts of intrinsic and extrinsic motivation play an important role in the literature on motivation and performance. Here, intrinsic motivation refers to doing something for its inherent satisfaction rather than for some separable consequence. Extrinsic motivation refers to doing something because it leads to a separable outcome (Ryan and Deci 2000 ).

Some studies have found that scientists are mainly intrinsically motivated (Jindal-Snape and Snape 2006 ; Lounsbury et al. 2012 ). Research interests, curiosity, and a desire to contribute to new knowledge are examples of such motivational factors. Intrinsic motives have also been shown to be crucial when people select research as a career choice (Roach and Sauermann 2010 ). Nevertheless, scientists are also motivated by extrinsic factors. Several European countries have adopted performance-based research funding systems (Zacharewicz et al. 2019 ). In these systems, researchers do not receive direct financial bonuses when they publish, although such practices may occur at local levels (Stephan et al. 2017 ). Therefore, extrinsic motivation for such researchers may include salary increases, peer recognitions, promotion, or expanded access to research resources (Lam 2011 ). According to Tien and Blackburn ( 1996 ), both types of motivations operate simultaneously, and their importance vary and may depend on the individual’s circumstances, personal situation, and values.

The extent to which different kinds of motivations play a role in scientists’ performance has been investigated in several studies. In these studies, bibliometric indicators based on the number of publications are typically used as outcome measures. Such indicators play a critical role in various contexts in the research system (Wilsdon et al. 2015 ), although it has also been pointed out that individuals can have different motivations to publish (Hangel and Schmidt-Pfister 2017 ).

Based on a survey of Romanian economics and business administration academics combined with bibliometric data, Horodnic and Zait ( 2015 ) found that intrinsic motivation was positively correlated with research productivity, while extrinsic motivation was negatively correlated. Their interpretations of the results are that researchers motivated by scientific interest are more productive, while researchers motivated by extrinsic forces will shift their focus to more financially profitable activities. Similarly, based on the observation that professors continue to publish even after they have been promoted to full professor, Finkelstein ( 1984 ) concluded that intrinsic rather than extrinsic motivational factors have a decisive role regarding the productivity of academics.

Drawing on a survey of 405 research scientists working in biological, chemical, and biomedical research departments in UK universities, Ryan ( 2014 ) found that (self-reported) variations in research performance can be explained by instrumental motivation based on financial incentives and internal motivation based on the individual’s view of themselves (traits, competencies, and values). In the study, instrumental motivation was found to have a negative impact on research performance: As the desire for financial rewards increase, the level of research performance decreases. In other words, researchers mainly motivated by money will be less productive and effective in their research. Contrarily, internal motivation was found to have a positive impact on research performance. This was explained by highlighting that researchers motivated by their self-concept set internal standards that become a reference point that reinforces perceptions of competency in their environments.

Nevertheless, it has also been argued that intrinsic and extrinsic motivations for publishing are intertwined (Ma 2019 ). According to Tien and Blackburn ( 1996 ), research productivity is neither purely intrinsically nor purely extrinsically motivated. Publication activity is often a result of research, which may be intrinsically motivated or motivated by extrinsic factors such as a wish for promotion, where the number of publications is often a part of the assessment (Cruz-Castro and Sanz-Menendez 2021 ; Tien 2000 , 2008 ).

The negative relationship between external/instrumental motivation and performance and the positive relationship between internal/self-concept motivation and performance are underlined by Ryan and Berbegal-Mirabent ( 2016 ). Drawing on a fuzzy set qualitative comparative analysis of a random sampling of 300 of the original respondents from Ryan ( 2014 ), they find that scientists working towards the standards and values they identify with, combined with a lack of concern for instrumental rewards, contribute to higher levels of research performance.

Based on the above, this article will address two research questions concerning different forms of motivation and the relationship between motivation and research performance.

How does the motivation of researchers vary across fields and countries?

How do different types of motivations affect research performance?

In this study, the roles of three different motivational factors are analysed. These are scientific curiosity, practical and societal applications, and career progress. The study aims to assess the role of these specific motivational factors and not the intrinsic-extrinsic distinction more generally. Of the three factors, scientific curiosity most strongly relates to intrinsic motivation; practical and societal applications also entail strong intrinsic aspects. On the other hand, career progress is linked to extrinsic motivation.

In addition to variation in researchers’ motivations by field and country, we consider differences in relation to age, position and gender. Additionally, when investigating how motivation relates to scientific performance we control for the influence of age, gender, country and funding. These are dimensions where differences might be found in motivational factors given that scientific performance, particularly publication productivity, has been shown to differ along these dimensions (Rørstad and Aksnes 2015 ).

Research context: three fields, five countries

To address the research question about potential differences across fields and countries, the study is based on a sample consisting of researchers in three different fields (cardiology, economics, and physics) and five countries (Denmark, Norway, Sweden, the Netherlands, and the UK). Below, we describe this research context in greater detail.

The fields represent three different domains of science: medicine, social sciences, and the natural sciences, where different motivational factors may be at play. This means that the fields cover three main areas of scientific investigations: the understanding of the world, the functioning of the human body, and societies and their functions. The societal role and mission of the fields also differ. While a primary aim of cardiology research and practice is to reduce the burden of cardiovascular disease, physics research may drive technology advancements, which impacts society. Economics research may contribute to more effective use of limited resources and the management of people, businesses, markets, and governments. In addition, the fields also differ in publication patterns (Piro et al. 2013 ). The average number of publications per researcher is generally higher in cardiology and physics than in economics (Piro et al. 2013 ). Moreover, cardiologists and physicists mainly publish in international scientific journals (Moed 2005 ; Van Leeuwen 2013 ). In economics, researchers also tend to publish books, chapters, and articles in national languages, in addition to international journal articles (Aksnes and Sivertsen 2019 ; van Leeuwen et al. 2016 ).

We sampled the countries with a twofold aim. On the one hand, we wanted to have countries that are comparable so that differences in the development of the science systems, working conditions, or funding availability would not be too large. On the other hand, we also wanted to assure variation among the countries regarding these relevant framework conditions to ensure that our findings are not driven by a specific contextual condition.

The five countries in the study are all located in the northwestern part of Europe, with science systems that are foremost funded by block grant funding from the national governments (unlike, for example, the US, where research grants by national funding agencies are the most important funding mechanism) (Lepori et al. 2023 ).

In all five countries, the missions of the universities are composed of a blend of education, research, and outreach. Furthermore, the science systems in Norway, Denmark, Sweden, and the Netherlands have a relatively strong orientation towards the Anglo-Saxon world in the sense that publishing in the national language still exists, but publishing in English in internationally oriented journals in which English is the language of publications is the norm (Kulczycki et al. 2018 ). These framework conditions ensure that those working in the five countries have somewhat similar missions to fulfil in their professions while also belonging to a common mainly Anglophone science system.

However, in Norway, Denmark, Sweden, and the Netherlands, research findings in some social sciences, law, and the humanities are still oriented on publishing in various languages. Hence, we avoided selecting the humanities field for this study due to a potential issue with cross-country comparability (Sivertsen 2019 ; Sivertsen and Van Leeuwen 2014 ; Van Leeuwen 2013 ).

Finally, the chosen countries vary regarding their level of university autonomy. When combining the scores for organisational, financial, staffing, and academic autonomy presented in the latest University Autonomy in Europe Scorecard presented by the European University Association (EUA), the UK, the Netherlands, and Denmark have higher levels of autonomy compared to Norway and Sweden, with Swedish universities having less autonomy than their Norwegian counterparts (Pruvot et al. 2023 ). This variation is relevant for our study, as it ensures that our findings are not driven by response from a higher education system with especially high or low autonomy, which can influence the motivation and satisfaction of academics working in it (Daumiller et al. 2020 ).

Data and methods

The data used in this article are a combination of survey data and bibliometric data retrieved from the WoS. The WoS database was chosen for this study due to its comprehensive coverage of research literature across all disciplines, encompassing the three specific research areas under analysis. Additionally, the WoS database is well-suited for bibliometric analyses, offering citation counts essential for this study.

Two approaches were used to identify the sample for the survey. Initially, a bibliometric analysis of the WoS using journal categories (‘Cardiac & cardiovascular systems’, ‘Economics’, and ‘Physics’) enabled the identification of key institutions with a minimum number of publications within these journal categories. Following this, relevant organisational units and researchers within these units were identified through available information on the units’ webpages. Included were employees in relevant academic positions (tenured academic personnel, post-docs, and researchers, but not PhD students, adjunct positions, guest researchers, or administrative and technical personnel).

Second, based on the WoS data, people were added to this initial sample if they had a minimum number of publications within the field and belonged to any of the selected institutions, regardless of unit affiliation. For economics, the minimum was five publications within the selected period (2011–2016). For cardiology and physics, where the individual publication productivity is higher, the minimum was 10 publications within the same period. The selection of the minimum publication criteria was based on an analysis of publication outputs in these fields between 2011 and 2016. The thresholds were applied to include individuals who are more actively engaged in research while excluding those with more peripheral involvement. The higher thresholds for cardiology and physics reflect the greater frequency of publications (and co-authorship) observed in these fields.

The benefit of this dual-approach strategy to sampling is that we obtain a more comprehensive sample: the full scope of researchers within a unit and the full scope of researchers that publish within the relevant fields. Overall, 59% of the sample were identified through staff lists and 41% through the second step involving WoS data.

The survey data were collected through an online questionnaire first sent out in October 2017 and closed in December 2018. In this period, several reminders were sent to increase the response rate. Overall, the survey had a response rate of 26.1% ( N = 2,587 replies). There were only minor variations in response rates between scientific fields; the variations were larger between countries. Tables 1 and 2 provide an overview of the response rate by country and field.

Operationalisation of motivation

Motivation was measured by a question in the survey asking respondents what motivates or inspires them to conduct research, of which three dimensions are analysed in the present paper. The two first answer categories were related to intrinsic motivation (‘Curiosity/scientific discovery/understanding the world’ and ‘Application/practical aims/creating a better society’). The third answer category was more related to extrinsic motivation (‘Progress in my career [e.g. tenure/permanent position, higher salary, more interesting/independent work]’). Appendix Table A1 displays the distribution of respondents and the mean value and standard deviation for each item.

These three different aspects of motivation do not measure the same phenomenon but seem to capture different aspects of motivation (see Pearson’s correlation coefficients in Appendix Table A2 ). There is no correlation between curiosity/scientific discovery, career progress, and practical application. However, there is a weak but significant positive correlation between career progress and practical application. These findings indicate that those motivated by career considerations to some degrees also are motivated by practical application.

In addition to investigating how researchers’ motivation varies by field and country, we consider the differences in relation to age, position and gender as well. Field of science differentiates between economics, cardiology, physics, and other fields. The country variables differentiate between the five countries. Age is a nine-category variable. The position variable differentiates between full professors, associate professors, and assistant professors. The gender variable has two categories (male or female). For descriptive statistics on these additional variables, see Appendix Table A3 .

Publication productivity and citation impact

To analyse the respondents’ bibliometric performance, the Centre for Science and Technology Studies (CWTS) in-house WoS database was used. We identified the publication output of each respondent during 2011–2017 (limited to regular articles, reviews, and letters). For 16% of the respondents, no publications were identified in the database. These individuals had apparently not published in international journals covered by the database. However, in some cases, the lack of publications may be due to identification problems (e.g. change of names). Therefore, we decided not to include the latter respondents in the analysis.

Two main performance measures were calculated: publication productivity and citation impact. As an indicator of productivity, we counted the number of publications for each individual (as author or co-author) during the period. To analyse the citation impact, a composite measure using three different indicators was used: total number of citations (total citations counts for all articles they have contributed to during the period, counting citations up to and including 2017), normalised citation score (MNCS), and proportion of publications among the 10% most cited articles in their fields (Waltman and Schreiber 2013 ). Here, the MNCS is an indicator for which the citation count of each article is normalised by subject, article type, and year, where 1.00 corresponds to the world average (Waltman et al. 2011 ). Based on these data, averages for the total publication output of each respondent were calculated. By using three different indicators, we can avoid biases or limitations attached to each of them. For example, using the MNCS, a respondent with only one publication would appear as a high impact researcher if this article was highly cited. However, when considering the additional indicator, total citation counts, this individual would usually perform less well.

The bibliometric scores were skewedly distributed among the respondents. Rather than using the absolute numbers, in this paper, we have classified the respondents into three groups according to their scores on the indicators. Here, we have used percentile rank classes (tertiles). Percentile statistics are increasingly applied in bibliometrics (Bornmann et al. 2013 ; Waltman and Schreiber 2013 ) due to the presence of outliers and long tails, which characterise both productivity and citation distributions.

As the fields analysed have different publication patterns, the respondents within each field were ranked according to their scores on the indicators, and their percentile rank was determined. For the productivity measure, this means that there are three groups that are equal in terms of number of individuals included: 1: Low productivity (the group with the lowest publication numbers, 0–33 percentile), 2: Medium productivity (33–67 percentile), and 3: High productivity (67–100 percentile). For the citation impact measure, we conducted a similar percentile analysis for each of the three composite indicators. Then everyone was assigned to one of the three percentile groups based on their average score: 1: Low citation impact (the group with lowest citation impact, 0–33 percentile), 2: Medium citation impact (33–67 percentile), and 3: High citation impact (67–100 percentile), cf. Table 3 . Although it might be argued that the application of tertile groups rather than absolute numbers leads to a loss of information, the advantage is that the results are not influenced by extreme values and may be easier to interpret.

Via this approach, we can analyse the two important dimensions of the respondents’ performance. However, it should be noted that the WoS database does not cover the publication output of the fields equally. Generally, physics and cardiology are very well covered, while the coverage of economics is somewhat lower due to different publication practices (Aksnes and Sivertsen 2019 ). This problem is accounted for in our study by ranking the respondents in each field separately, as described above. In addition, not all respondents may have been active researchers during the entire 2011–2017 period, which we have not adjusted for. Despite these limitations, the analysis provides interesting information on the bibliometric performance of the respondents at an aggregated level.

Regression analysis

To analyse the relationship between motivation and performance, we apply multinomial logistic regression rather then ordered logistic regression because we assume that the odds for respondents belonging in each category of the dependent variables are not equal (Hilbe 2017 ). The implication of this choice of model is that the model tests the probability of respondents being in one category compared to another (Hilbe 2017 ). This means that a reference or baseline category must be selected for each of the dependent variables (productivity and citation impact). Furthermore, the coefficient estimates show how the probability of being in one of the other categories decreases or increases compared to being in the reference category.

For this analysis, we selected the medium performers as the reference or baseline category for both our dependent variables. This enables us to evaluate how the independent variables affect the probability of being in the low performers group compared to the medium performers and the high performers compared to the medium performers.

To evaluate model fit, we started with a baseline model where only types of motivations were included as independent variables. Subsequently, the additional variables were introduced into the model, and based on measures for model fit (Pseudo R 2 , -2LL, and Akaike Information Criterion (AIC)), we concluded that the model with all additional variables included provides the best fit to the data for both the dependent variables (see Appendix Tables A5 and A6 ). Additional control variables include age, gender, country, and funding. We include these variables as controls to obtain robust effects of motivation and not effects driven by other underlying factors. The type of funding was measured by variables where the respondent answered the following question: ‘How has your research been funded the last five years?’ The funding variable initially consisted of four categories: ‘No source’, ‘Minor source’, ‘Moderate source’, and ‘Major source’. In this analysis, we have combined ‘No source’ and ‘Minor source’ into one category (0) and ‘Moderate source’ and ‘Major source’ into another category (1). Descriptive statistics for the funding variables are available in Appendix Table A4 . We do not control for the influence of field due to how the scientific performance variables are operationalised, the field normalisation implies that there are no variations across fields. We also do not control for position, as this variable is highly correlated with age, and we are therefore unable to include these two variables in the same model.

The motivation of researchers

In the empirical analysis, we first investigate variation in motivation and then relate it to publications and citations as our two measures of research performance.

As Fig. 1 shows, the respondents are mainly driven by curiosity and the wish to make scientific discoveries. This is by far the most important motivation. Practical application is also an important source of motivation, while making career progress is not identified as being very important.

Motivation of researchers– percentage

As Table 4 shows, at the level of fields, there are no large differences, and the motivational profiles are relatively similar. However, physicists tend to view practical application as somewhat less important than cardiologists and economists. Moreover, career progress is emphasised most by economists. Furthermore, as table 5 shows, there are some differences in motivation between countries. For curiosity/scientific discovery and practical application, the variations across countries are minor, but researchers in Denmark tend to view career progress as somewhat more important than researchers in the other countries.

Furthermore, as table 6 shows, women seem to view practical application and career progress as a more important motivation than men; these differences are also significant. Similar gender disparities have also been reported in a previous study (Zhang et al. 2021 ).

There are also some differences in motivation across the additional variables worth mentioning, as Table 7 shows. Unsurprisingly, perhaps, there is a significant moderate negative correlation between age, position, and career progress. This means that the importance of career progress as a motivation seems to decrease with increased age or a move up the position hierarchy.

In the second part of the analysis, we relate motivation to research performance. We first investigate publications and productivity using the percentile groups. Here, we present the results we use using predicted probabilities because they are more easily interpretable than coefficient estimates. For the model with productivity percentile groups as the dependent variable, the estimates for career progress were negative when comparing the medium productivity group to the high productivity group and the medium productivity group to the low productivity group. This result indicates that the probability of being in the high and low productivity groups decreases compared to the medium productivity group as the value of career progress increases, which may point towards a curvilinear relationship between the variables. A similar pattern was also found in the model with the citation impact group as the dependent variable, although it was not as apparent.

As a result of this apparent curvilinear relationship, we included quadric terms for career progress in both models, and these were significant. Likelihood ratio tests also show that the models with quadric terms included have a significant better fit to the data. Furthermore, the AIC was also lower for these models compared to the initial models where quadric terms were not included (see Appendix Tables A5 – A7 ). Consequently, we base our results on these models, which can be found in Appendix Table A7 . Due to a low number of respondents in the low categories of the scientific curiosity/discovery variable, we also combined the first three values into one to include it as a variable in the regression analysis, which results in a reduced three-value variable for scientific curiosity/discovery.

Results– productivity percentile group

Using the productivity percentile group as the dependent variable, we find that the motivational aspects of practical application and career progress have a significant effect on the probability of being in the low, medium, or high productivity group but not curiosity/scientific discovery. In Figs. 2 and 3 , each line represents the probability of being in each group across the scale of each motivational aspect.

Predicted probability for being in each of the productivity groups according to the value on the ‘practical application’ variable

Predicted probability of being in the low and high productivity groups according to the value on the ‘progress in my career’ variable

Figure 2 shows that at low values of application, there are no significant differences between the probability of being in either of the groups. However, from around value 3 of application, the differences between the probability of being in each group increases, and these are also significant. As a result, we concluded that high scores on practical application is related to increased probability of being in the high productivity group.

In Fig. 3 , we excluded the medium productivity group from the figure because there are no significant differences between this group and the high and low productivity group. Nevertheless, we found significant differences between the low productivity and the high productivity group. Since we added a quadric term for career progress, the two lines in Fig. 3 have a curvilinear shape. Figure 3 shows that there are only significant differences between the probability of being in the low or high productivity group at mid and high values of career progress. In addition, the probability of being in the high productivity group is at its highest value at mid values of career progress. This indicates that being motivated by career progress increases the probability of being in the high productivity group but only up to a certain point before it begins to have a negative effect on the probability of being in this group.

We also included age and gender as variables in the model, and Figs. 4 and 5 show the results. Figure 4 shows that age especially impacts the probability of being in the high productivity and low productivity groups. The lowest age category (< 30–34 years) has the highest probability for being in the low productivity group, while from the mid age category (50 years and above), the probability is highest for being in the high productivity group. This means that increased age is related to an increased probability of high productivity. The variable controlling for the effect of funding also showed some significant results (see Appendix Table A7 ). The most relevant finding is that receiving competitive grants from external public sources had a very strong and significant positive effect on being in the high productivity group and a medium-sized significant negative effect on being in the low productivity group. This shows that receiving external funding in the form of competitive grants has a strong effect on productivity.

Predicted probability of being in each of the productivity groups according to age

Figure 5 shows that there is a difference between male and female respondents. For females, there are no differences in the probability of being in either of the groups, while males have a higher probability of being in the high productivity group compared to the medium and low productivity groups.

Results– citation impact group

For the citation impact group as the dependent variable, we found that career progress has a significant effect on the probability of being in the low citation impact group or the high citation group but not curiosity/scientific discovery or practical application. Figure 6 shows how the probability of being in the high citation impact group increases as the value on career progress increases and is higher than that of being in the low citation impact group, but only up to a certain point. This indicates that career progress increases the probability of being in the high citation impact group to some degree but that too high values are not beneficial for high citation impact. However, it should also be noted that the effect of career progress is weak and that it is difficult to conclude on how very low or very high values of career progress affect the probability of being in the two groups.

Predicted probability for being in each of the citation impact groups according to the value on the ‘progress in my career’ variable

We also included age and gender as variables in the model, and we found a similar pattern as in the model with productivity percentile group as the dependent variable. However, the relationship between the variables is weaker in this model with the citation impact group as the dependent variable. Figure 7 shows that the probability of being in the high citation impact group increases with age, but there is no significant difference between the probability of being in the high citation impact group and the medium citation impact group. We only see significant differences when each of these groups is compared to the low citation impact group. In addition, the increase in probability is more moderate in this model.

Predicted probability of being in each of the citation impact groups according to age

Figure 8 shows that there are differences between male and female respondents. Male respondents have a significant higher probability of being in the medium or high citation impact group compared to the low citation impact group, but there is no significant difference in the probability between the high and medium citation impact groups. For female respondents, there are no significant differences. Similarly, for age, the effect also seems to be more moderate in this model compared to the model with productivity percentile groups as the dependent variable. In addition, the effect of funding sources is more moderate on citation impact compared to productivity (see Appendix Table A7 ). Competitive grants from external public sources still have the most relevant effect, but the effect size and level of significance is lower than for the model where productivity groups are the dependent variable. Respondents who received a large amount of external funding through competitive grants are more likely to be highly cited, but the effect size is much smaller, and the result is only significant at p < 0.1. Those who do not receive much funding from this source are more likely to be in the low impact group. Here, the effect size is large, and the coefficient is highly significant.

Predicted probability for being in each of the citation impact groups according to gender

Concluding discussion

This article aimed to explore researchers’ motivations and investigate the impact of motivation on research performance. By addressing these issues across several fields and countries, we provided new evidence on the motivation and performance of researchers.

Most researchers in our large-N survey found curiosity/scientific discovery to be a crucial motivational factor, with practical application being the second most supported aspect. Only a smaller number of respondents saw career progress as an important inspiration to conduct their research. This supports the notion that researchers are mainly motivated by core aspects of academic work such as curiosity, discoveries, and practical application of their knowledge and less so by personal gains (see Evans and Meyer 2003 ). Therefore, our results align with earlier research on motivation. In their interview study of scientists working at a government research institute in the UK, Jindal-Snape and Snape ( 2006 ) found that the scientists were typically motivated by the ability to conduct high quality, curiosity-driven research and de-motivated by the lack of feedback from management, difficulty in collaborating with colleagues, and constant review and change. Salaries, incentive schemes, and prospects for promotion were not considered a motivator for most scientists. Kivistö and colleagues ( 2017 ) also observed similar patterns in more recent survey data from Finnish academics.

As noted in the introduction, the issue of motivation has often been analysed in the literature using the intrinsic-extrinsic distinction. In our study, we have not applied these concepts directly. However, it is clear that the curiosity/scientific discovery item should be considered a type of intrinsic motivation, as it involves performing the activity for its inherent satisfaction. Moreover, the practical application item should probably be considered mainly intrinsic, as it involves creating a better society (for others) without primarily focusing on gains for oneself. The career progress item explicitly mentions personal gains such as position and higher salary and is, therefore, a type of extrinsic motivation. This means that our results support the notion that there are very strong elements of intrinsic motivation among researchers (Jindal-Snape and Snape 2006 ).

When analysing the three aspects of motivation, we found some differences. Physicists tend to view practical application as less important than researchers in the two other fields, while career progress was most emphasised by economists. Regarding country differences, our data suggest that career progress is most important for researchers in Denmark. Nevertheless, given the limited effect sizes, the overall picture is that motivational factors seem to be relatively similar regarding disciplinary and country dimensions.

Regarding gender aspects of motivation, our data show that women seem to view practical application and career progress as more important than men. One explanation for this could be the continued gender differences in academic careers, which tend to disadvantage women, thus creating a greater incentive for female scholars to focus on and be motivated by career progress aspects (Huang et al. 2020 ; Lerchenmueller and Sorenson 2018 ). Unsurprisingly, respondents’ age and academic position influenced the importance of different aspects of motivation, especially regarding career progress. Here, increased age and moving up the positional hierarchy are linked to a decrease in importance. This highlights that older academics and those in more senior positions drew more motivation from other sources that are not directly linked to their personal career gains. This can probably be explained by the academic career ladder plateauing at a certain point in time, as there are often no additional titles and very limited recognition beyond becoming a full professor. Finally, the type of funding that scholars received also had an influence on their productivity and, to a certain extent, citation impact.

Overall, there is little support that researchers across various fields and countries are very different when it comes to their motivation for conducting research. Rather, there seems to be a strong common core of academic motivation that varies mainly by gender and age/position. Rather than talking about researchers’ motivation per se, our study, therefore, suggests that one should talk about motivation across gender, at different stages of the career, and, to a certain degree, in different fields. Thus, motivation seems to be a multi-faceted construct, and the importance of different aspects of motivation vary between different groups.

In the second step of our analysis, we linked motivation to performance. Here, we focused on both scientific productivity and citation impact. Regarding the former, our data show that both practical application and career progress have a significant effect on productivity. The relationship between practical application aspects and productivity is linear, meaning that those who indicate that this aspect of motivation is very important to them have a higher probability of being in the high productivity group. The relationship between career aspects of motivation and productivity is curve linear, and we found only significant differences between the high and low productivity groups at mid and high values of the motivation scale. This indicates that being more motivated by career progress increases productivity but only to a certain extent before it starts having a detrimental effect. A common assumption has been that intrinsic motivation has a positive and instrumental effect and extrinsic motivation has a negative effect on the performance of scientists (Peng and Gao 2019 ; Ryan and Berbegal-Mirabent 2016 ). Our results do not generally support this, as motives related to career progress are positively linked with productivity only to a certain point. Possibly, this can be explained by the fact that the number of publications is often especially important in the context of recruitment and promotion (Langfeldt et al. 2021 ; Reymert et al. 2021 ). Thus, it will be beneficial from a scientific career perspective to have many publications when trying to get hired or promoted.

Regarding citation impact, our analysis highlights that only the career aspects of motivation have a significant effect. Similar to the results regarding productivity, being more motivated by career progress increases the probability of being in the high citation impact group, but only to a certain value when the difference stops being significant. It needs to be pointed out that the effect strength is weaker than in the analysis that focused on productivity. Thus, these results should be treated with greater caution.

Overall, our results shed light on some important aspects regarding the motivation of academics and how this translates into research performance. Regarding our first research question, it seems to be the case that there is not one type of motivation but rather different contextual mixes of motivational aspects that are strongly driven by gender and the academic position/age. We found only limited effects of research fields and even less pronounced country effects, suggesting that while situational, the mix of motivational aspects also has a common academic core that is less influenced by different national environments or disciplinary standards. Regarding our second research question, our results challenge the common assumption that intrinsic motivation has a positive effect and extrinsic motivation has a negative effect on the performance of scientists. Instead, we show that motives related to career are positively linked to productivity at least to a certain point. Our analysis regarding citation patterns achieved similar results. Combined with the finding regarding the importance of current academic position and age for specific patterns of motivation, it could be argued that the fact that the number of publications is often used as a measurement in recruitment and promotion makes academics that are more driven by career aspects publish more, as this is perceived as a necessary condition for success.

Our study has a clear focus on the research side of academic work. However, most academics do both teaching and research, which raises the question of how far our results can also inform our knowledge regarding the motivation for teaching. On the one hand, previous studies have highlighted that intrinsic motivation is also of high importance for the quality of teaching (see e.g. Wilkesmann and Lauer 2020 ), which fits well with our findings. At the same time, the literature also highlights persistent goal conflicts of academics (see e.g. Daumiller et al. 2020 ), given that extra time devoted to teaching often comes at the costs of publications and research. Given that other findings in the literature show that research performance continues to be of higher importance than teaching in academic hiring processes (Reymert et al. 2021 ), the interplay between research performance, teaching performance, and different types of motivation is most likely more complicated and demands further investigation.

While offering several relevant insights, our study still comes with certain limitations that must be considered. First, motivation is a complex construct. Thus, there are many ways one could operationalise it, and not one specific understanding so far seems to have emerged as best practice. Therefore, our approach to operationalisation and measurement should be seen as an addition to this broader field of measurement approaches, and we do not claim that this is the only sensible way of doing it. Second, we rely on self-reported survey data to measure the different aspects of motivation in our study. This means that aspects such as social desirability could influence how far academics claim to be motivated by certain aspects. For example, claiming to be mainly motivated by personal career gains may be considered a dubious motive among academics.

With respect to the bibliometric analyses, it is important to realise that we have lumped researchers into categories, thereby ‘smoothening’ the individual performances into group performances under the various variables. This has an effect that some extraordinary scores might have become invisible in our study, which might have been interesting to analyse separately, throwing light on the relationships we studied. However, breaking the material down to the lower level of analysis of individual researchers also comes with a limitation, namely that at the level of the individual academic, bibliometrics tend to become quite sensitive for the underlying numbers, which in itself is then hampered by the coverage of the database used, the publishing cultures in various countries and fields, and the age and position of the individuals. Therefore, the level of the individual academic has not been analysed in our study, how interesting and promising outcomes might have been. even though we acknowledge that such a study could yield interesting results.

Finally, our sample is drawn from northwestern European countries and a limited set of disciplines. We would argue that we have sufficient variation in countries and disciplines to make the results relevant for a broader audience context. While our results show rather small country or discipline differences, we are aware that there might be country- or discipline-specific effects that we cannot capture due to the sampling approach we used. Moreover, as we had to balance sufficient variation in framework conditions with the comparability of cases, the geographical generalisation of our results has limitations.

This article investigated what motivates researchers across different research fields and countries and how this motivation influences their research performance. The analysis showed that the researchers are mainly motivated by scientific curiosity and practical application and less so by career considerations. Furthermore, the analysis shows that researchers driven by practical application aspects of motivation have a higher probability of high productivity. Being driven by career considerations also increases productivity but only to a certain extent before it starts having a detrimental effect.

The article is based on a large-N survey of economists, cardiologists, and physicists in Denmark, Norway, Sweden, the Netherlands, and the UK. Building on this study, future research should expand the scope and study the relationship between motivation and productivity as well as citation impact in a broader disciplinary and geographical context. In addition, we encourage studies that develop and validate our measurement and operationalisation of aspects of researchers’ motivation.

Finally, a long-term panel study design that follows respondents throughout their academic careers and investigates how far their motivational patterns shift over time would allow for more fine-grained analysis and thereby a richer understanding of the important relationship between motivation and performance in academia.

Data availability

The data set for this study is available from the corresponding author upon reasonable request.

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Acknowledgements

We are thankful to the R-QUEST team for input and comments to the paper.

The authors disclosed the receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Research Council Norway (RCN) [grant number 256223] (R-QUEST).

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Silje Marie Svartefoss

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Silje Marie Svartefoss & Dag W. Aksnes

Department of Political Science, University of Oslo, 0315, Oslo, Norway

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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Silje Marie Svartefoss, Jens Jungblut, Dag W. Aksnes, Kristoffer Kolltveit, and Thed van Leeuwen. The first draft of the manuscript was written by all authors in collaboration, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Svartefoss, S.M., Jungblut, J., Aksnes, D.W. et al. Explaining research performance: investigating the importance of motivation. SN Soc Sci 4 , 105 (2024). https://doi.org/10.1007/s43545-024-00895-9

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The Health and Clinical Outcomes Research, Health Data Science Student Spotlight Series: Nitin Katakam (‘24)

Nitin Katakam (’24) is a second-year student in the master of health data science program in the Saint Louis University School of Medicine.

Young, Indian man in grey suit and glasses

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Initially, the realm of research seemed daunting to me, yet an opportunity presented by a professor during my clinical rotations sparked a profound interest that has persisted ever since. Delving into health data science appeared as the perfect avenue to immerse myself fully in research methodologies. It promised to equip me with skills in the statistical aspects of research—a component often met with apprehension by many clinicians. This realization guided me toward this course.

What advice would you give to incoming students interested in HDS?

Two words: REACH OUT. Please reach out to your faculty. They are very friendly and willing to help you. If they can't, they will direct you to someone who can. You will not be overlooked. Other than this, I would say be thorough with your coursework. You don’t have to be perfect with what you learn. All that is expected of you is a decent, honest effort. Most times, that is all you need. Also bear in mind that the coursework touches upon all the necessary concepts for a data scientist, but it is on you to build on those concepts.

What are your future aspirations or career plans upon completing the program and what job title will you be pursuing

I aim to work as a research analyst within clinical research upon graduation and would like to work up to a research scientist position. I think traditional research is evolving and embracing data science more by the year. There's lots of potential here.

How would you describe what ‘health data science’ is to someone who has not heard of it before?

My answer to this has definitely evolved over time. But to put it simply, it is statistics on steroids. We clean, analyze, make predictions and present our findings about data to improve health care. For instance, if we notice a spike in common cold cases, we don’t just count them. We dig deeper: Is this spike normal? How fast are cases rising? What might happen next? We can do this normally. But, let's say we want to predict/analyze such trends at a nationwide scale with hundreds of thousands, or even millions, of data points. That’s where health data science stands out, but it’s so much more!

Why is the field of health data science important?

I think it is at the forefront of medical research, unlocking the power of vast datasets — from thousands to billions of data points — to refine our understanding and decision-making in health care. Such statistical power is invaluable in medicine, a field where a false negative or a false positive can mean/cost a lot.

Can you share a memorable experience or project from your time in the program?

One of my most memorable projects was a geomapping analysis focused on the visualization of smoking trends, marijuana use, the area deprivation index (ADI), and their correlations with cancer. I accurately predicted drug overdose deaths, highlighting significant regional health disparities. My statistical analysis — using Mann-Whitney U and chi-squared tests — revealed significant correlations between various factors and cancer incidence across different states. I personally like it because it is my most aesthetically pleasing project due to the heatmaps and trend charts.

What skills or knowledge have you gained that you believe will benefit your future career?

I think the attitude of approaching any problem/project with a willingness to learn is what has rewarded me the most in my research projects. I've also developed strong technical skills in data analysis and visualization using tools like R, BigQuery and Python. Additionally, my medical background and research experience have equipped me with the knowledge to apply data science effectively in health care contexts.

Is there anything else you'd like to share with fellow students and alumni about your journey in HDS?

The faculty are the best part about the program. They absolutely love it when you are proactive and will go a long way to help you grow. It's been amazing to see the department evolve, welcoming more brilliant minds into the faculty recently. Plus, if you're ever in need of a quiet spot to hit the books, the department offers a great study space that's pretty much a bonus.

About the Health Data Science, M.S.

Saint Louis University's Master of Science in Health Data Science is designed to prepare students for a career in today's data-driven health care industry. Successful data scientists possess an artful ability to blend, synthesize and communicate data for use in clinical decisions by patients and providers, as well as advancing quality improvement efforts across health systems.

View more information

About the Department of Health and Clinical Outcomes Research

The mission of the Department of Health and Clinical Outcomes Research is to serve as the collaborative bridge between divisions, departments, and colleges/schools across medicine and the health sciences to support methodologically rigorous research to solve complex health problems. The Department of Health and Clinical Outcomes Research is a scholarly community of faculty, staff and students committed to strengthening the delivery and outcomes of medical care through education and training programs, innovative research, and consulting services.

Money: Why are concert tickets so expensive? Here's who is really responsible

Ticket prices for some concerts have reached astronomical levels in recent years - we've looked at why and who is profiting. Read this and the rest of our Weekend Money content below and join us for live updates again from Monday.

Saturday 1 June 2024 07:51, UK

Taylor Swift

Weekend Money

Where is all the money going? Here's who is really responsible for concert tickets going crazy
Strikes, new bank notes, cat fines and airport disruption: Main June money dates for your calendar
Your comments: Man Utd WFH crackdown, Sterling's uni pledge, pebble fines and standing charges

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By Katie Williams , Money team

Spending a fair chunk on going to see your favourite big artist is not new - but it certainly feels like concert prices have entered a new stratosphere.

Fans of Bruce Springsteen have paid upwards of £120 for "rear pitch" standing tickets for his May 2024 tour, while some expressed disappointment recently over the £145 price tag of standing tickets for Billie Eilish's 2025 UK leg.

And while you could have nabbed Beyonce or Taylor Swift tickets in the UK for £50 (before fees) if you took a "nosebleed" seat, these had limited availability and quickly sold out. General admission standing tickets for Swift's Eras tour - which comes to the UK next week - started at £110.40 and those at the front had to shell out £172.25. It didn't stop there - by the time many fans got to the front of the online ticket queue, the only tickets left cost upwards of £300.

So what's behind rising ticket costs? These are some of the reasons...

Fans willing to pay for big spectacles

Simply put, ticket prices would come down if people voted with their feet.

Matt Hanner, booking agent and operations director at Runway, said prices at the top level had "risen considerably" - but the increase was partly being driven by demand.

"We're seeing a lot more stadium shows, greenfield, outdoor festival-type shows which are now a staple of towns around the country," he said.

"There's a growing number of people that are happy to spend a large chunk of their disposable income on going to a major music event."

Jon Collins, chief executive of LIVE, the trade body representing the UK's live music industry, had a similar view.

He said there were more large-scale shows and tours now than ever, and there was "massive appetite" among music lovers for "bigger spectacles".

Fancy shows mean higher costs - with staffing, the price of the venue, transport, artists' needs, insurance and loads more to factor in.

Of course, all these things are affected by inflation. Collins said ticket prices also factored in the rising costs that had hit every venue from the grassroots scene to major arenas.

"You've got a couple of different factors - you've got the spectacle of the show and the production cost and everything that goes into the ticket price. But then you've also got the fundamentals," he said.

The cost of venue hire has increased "significantly" in the past couple of years due to electricity and gas price rises, he added.

"You've got the increase in the cost of people… very justifiable costs like increases in minimum wage and living wage. At every stage of the process we've got these cost increases that will all push through the pressure on the ticket price."

Are artists being greedy?

How much money artists really earn off live touring is of interest to many - but the music industry is generally reluctant to release details.

The people we spoke to suggested it was not as simple as artist greed because, as we mentioned earlier, there's a lot to pay for before anything reaches their bank accounts.

The Guardian spoke to anonymous insiders about this topic in 2017. Its report suggested that between 50-70% of gross earnings were left for promoters and artists. The piece also cited a commonly quoted figure that the promoter takes 15% of what is left and the act will get 85%.

It all depends on the calibre of the artist and how much work the promoter has had to put in - they could end up with a bigger share if it was a hard push to get the show sold.

The people we spoke to said music acts and their teams would discuss the ticket price, and the bigger the act, the more sway they have - but it's ultimately set by the promoter.

Taylor Swift - arguably the biggest popstar on the planet right now - is personally earning between $10m and $13m (£8m - £10.5m) on every stop of her Eras Tour, according to Forbes. She is reported to take home a whopping 85% of all revenue from the tour.

But it's worth pointing out, too, that she's been known to be generous with her cash, having given $100,000 bonuses to the dozens of lorry drivers working on the tour.

What have other artists said?

Some artists have been critical of the high ticket prices being demanded by others.

Tom Grennan told ITV two years ago that he had seen "loads of artists putting tickets out that are way too expensive for the times that we are in", adding that he wanted people to enjoy shows without worrying if they could pay their bills.

Singer-songwriter Paul Heaton was also praised for capping ticket prices for his tour with Jacqui Heaton at £30 in a bid to tackle music industry "greed" and help people during the cost of living.

British star Yungblud recently announced his own music festival, Bludfest - saying the industry was too expensive and needed to be "shaken up".

"I believe that gigs are too expensive, festivals are too expensive, and I just wanted to work to create something that has been completely done by me," he told Sky News.

Meanwhile, frequent Swift collaborator Jack Antonoff has said "dynamic pricing" by ticket sale sites such as Ticketmaster was also an issue when it came to cost.

He told Stereogum that he wanted artists to be able to opt out of the system - which basically means ticket prices increase when a show is in demand - and be able to sell them at the price they choose.

On its website, Ticketmaster describes its "Platinum" tickets as those that have their price adjusted according to supply and demand.

It says the goal of the dynamic pricing system is to "give fans fair and safe access to the tickets, while enabling artists and other people involved in staging live events to price tickets closer to their true market value".

The company claims it is artists, their teams and promoters who set pricing and choose whether dynamic pricing is used for their shows.

Ticketing website fees

As well as dynamic pricing, "sneaky" fees by online ticket sites are also causing issues for live music lovers, according to the consumer champion Which?.

A report from the group last month said an array of fees that isn't seen until checkout can add around 20% to the cost of concert and festival tickets.

Which? has urged a crackdown on the "bewildering" extra charges, which include booking, "delivery" and "transaction" fees, venue charges and sometimes charges for e-tickets.

The Cure lead singer Robert Smith tweeted that he was "sickened" after fans complained last year about processing fees on Ticketmaster that wound up costing more than the ticket itself in some cases.

Responding to the Which? findings, Ticketmaster (which was far from the only company named) said: "Fees are typically set by and shared with our clients… who all invest their skill, resource and capital into getting an event off the ground. Ticketmaster supports legislation that requires all-in pricing across the industry."

Live Nation and Ticketmaster sued over 'dominance'

The US government is suing Ticketmaster owner Live Nation over allegations the company is "monopolising" the live events industry.

Justice department officials said it was unfair for the firm to control around 70% of primary ticketing for concerts in America.

Live Nation has been accused of using lengthy contracts to prevent venues from choosing rival ticket companies, blocking venues from using multiple ticket sellers and threatening venues that they could lose money and support if Ticketmaster wasn't the chosen seller.

Live Nation said the lawsuit reflected a White House that had turned over competition enforcement "to a populist urge that simply rejects how antitrust law works".

"Some call this 'anti-monopoly', but in reality it is just anti-business," it said.

And it said its share of the market had been shrinking and its profit margin of 1.4% was the "opposite of monopoly power".

The lawsuit "won't solve the issues fans care about relating to ticket prices, service fees and access to in-demand shows", the company said.

"We will defend against these baseless allegations, use this opportunity to shed light on the industry and continue to push for reforms that truly protect consumers and artists."

As well as reportedly controlling most of the ticketing market, Live Nation also owns and represents some acts and venues.

Canadian artist Dan Mangan told Moneywise this was enabling the company to take "more and more of the pie".

He said when venue rent, equipment and other costs were taken into account, lesser known artists could take as little as 20% of ticket sales.

Another major cost on tickets in the UK is VAT (value added tax).

At 20%, it's pretty hefty. It was brought down to 5% and then 12.5% as the live music industry was hampered by COVID, but returned to the pre-pandemic level in April 2022.

The charge puts the UK "out of step" with other countries, Collins said.

"In competitive major markets like France, it's 5%. Germany it's 7%, Italy it's 10%. Sales tax in the US is typically 6% or 7%. So we are significantly out of step with other markets when it comes to how much VAT we charge on tickets," he said.

Touring now bigger source of income for major stars

With the decline of physical products and the rise of subscription listening, artists are earning less from making music - and income from live shows has become more important for the biggest stars.

Writer and broadcaster Paul Stokes said major stars who would have toured infrequently in the past were now willing to put on more shows as it becomes increasingly profitable.

Some artists will even pencil in multiple nights at huge venues like Wembley Arena, he said - something that wouldn't have been considered two decades ago.

"When Wembley was built and they said 'we'll be doing regular shows' you'd think 'are there acts big enough to fill this massive stadium?'

"It's become absolutely part of the live calendar that artists will come and play not just one night at Wembley, but two or three every every summer."

Stokes said this demand has also prompted the scale of shows that we've become used to seeing, featuring expensive production and pyrotechnics.

Not being felt evenly

While a night out seeing a platinum-selling artist is likely to be an expensive affair, industry figures are also keen to point out that the escalation in ticket prices isn't necessarily happening at a lower level.

Collins said that while major stars were putting on arena shows, there would be plenty of other live music taking place at the same time, "from the free pub gig to the £10 ticket at the grassroots venue, to the £30 mid-cap".

"There's an absolute range of opportunities for people to experience live music, from free through to experiencing the biggest stars on the planet," he said.

But concertgoers choosing to save their cash for artists they're more familiar with may have led to a "suppression" of prices for lesser-known acts, Hanner noted.

"Everyone's short of disposable income because there's a cost of living crisis. [Artists' and promoters'] core costs are going up as well, so it's more expensive for everyone. That fear of pricing people out is just being compounded," he said.

"I think [that] has definitely led to prices being suppressed [at the lower level], when really they should have been going up."

With May in the rearview mirror, here are the key money dates for your calendar in June.

1 June onwards - benefit changes

While benefits rose 6.7% from 8 April for many claimants, those who had their last assessment period before then will have had to wait until June to receive the new, higher rate.

The exact date in June when that payment is made will depend on when you were assessed.

Also from 1 June, all people claiming Housing Benefit alone will be asked to claim Universal Credit instead within three months of receiving the letter.

Failure to do so could result in you losing your entitlement.

1-2 June - Heathrow disruption

Hundreds of border force officers at Heathrow Airport are striking until Sunday in a dispute over rosters.

More than 500 of its members working on passport control at terminals 2, 3, 4 and 5 are taking action.

Disruption is expected over the weekend as families return to the UK at the end of the half-term holiday.

5 June - new banknotes

Banknotes featuring the face of the King will enter circulation across the UK.

Notes that feature the portrait of the late Queen will remain legal tender and will co-circulate.

The new banknotes will only be printed to replace those that are worn and to meet any overall increase in demand.

10 June - £500 cat fines

All cats over 20 weeks old in England must be microchipped by 10 June.

You could face a £500 if you miss the deadline and don't get your cat microchipped in the following 21 days.

The law does not apply to the rest of the UK.

16 June - Father's Day

As the day dedicated to dads and father figures approaches, it may be worth remembering to put some cash aside to treat them in mid-June.

19 June - inflation data released

We'll get May's inflation data in the monthly drop from the Office for National Statistics.

This will give us the clearest indication of whether the Bank of England will lower interest rates.

Remember, the Bank's target is 2% (April's headline rate was 2.3%), so the closer we get to that number the better.

20 June - interest rate decision

Another Monetary Policy Committee meeting at the Bank of England will determine whether we finally get a drop in interest rates.

Many economists predict a cut from 5.25% will happen in August, but June isn't ruled out.

27 June - doctors' strike

Junior doctors in England will begin a five-day strike at 7am over pay.

The last strike by junior doctors led to 91,048 appointments, operations and procedures being postponed.

30 June - meter readings

Not a fixed date - more of a reminder.

From 1 July, the energy price cap will fall by £122 per year.

Your provider will do most of the work, but you can help keep your bill accurate by submitting meter readings (unless you have a smart meter) ahead of this date.

The big topics covered in the Money blog this week that got you commenting were...

Manchester United giving staff who don't want to come into the office a week to resign
Raheem Sterling offering to pay for 14 people to go to university
Fines for pebble-taking tourists on beaches
The standing charge rising despite the energy price cap being cut

Let's start with the two football-related stories.

Sir Jim Ratcliffe, new part-owner of Manchester United, sent an email round on Tuesday offering all non-playing staff the chance to resign (with their annual bonus paid early) within the week if they do not like his plan to stop working from home ...

Some praised his decision...

Well done Sir Jim Ratcliffe. Finally, somebody who has the guts to stand up and end this 'working from home' nonsense! edwinbasnett

Sir Jim has got it right, decisions are decisive and provide clear expectations and an option to get out. WFH doesn't work at the levels seen following COVID, I'm sure it does for some but many take advantage and it's far more difficult to manage. Tel

Others not so much...

Thankfully there's not quite so stark an ultimatum from my employer, but I am planning to leave soon. It's a nonsense commuting to an office where I then engage with other colleagues over Teams/Zoom. Jim

Who wants to work for a **** like that anyway with that attitude? No filter

Earlier in the week, we learnt Raheem Sterling will financially support 14 students through university.

Applications for the Raheem Sterling Foundation Scholarship Programme - which closed on Thursday - were open to students of black, African and Caribbean heritage from socio-economically under-represented backgrounds to help bridge the equality gap.

This will be the second year the Chelsea forward will assist successful applicants at King's College London and the University of Manchester.

Readers said...

Sterling is a credit to sport, football and his heritage. I hope more footballers will join him and his endeavours. Judy

This is brilliant - I have never understood why professionals in many fields do not give more back to their communities. Just a visit to their old primary school could turn a bright light on for so many kids. Why don't many more do it? Old white woman

Well done Raheem Sterling for financially supporting 14 students who would like to attend university. Sometimes professional football players get a negative press but this is amazing, well done. Anthony G

Away from football and to Cumbria - where beach-goers have been warned they could face a fine of up to £1,000 if they remove pebbles or shells across the area.

You said...

Why aren't the same rules applied to stop Southern Water dumping all their s*** into our seas. They take millions of pounds from normal people who trust them to process it correctly. Anti s outhern water

So that means the thrill of going to the beach and collecting a few shells is stopped. What about the scallop shells used in restaurants and supermarkets? What about the sacks of shells sold at garden centres? What about the tonnes of sand used every day etc etc? JR

Has the world gone mad? £1,000 fine for taking pebbles home from a beach? I think most children take a few pebbles home with them. Bob

Many of you responded to last Friday's announcement that while the energy price cap would fall in July, standing charges - the set amount you pay for gas and electric each day regardless of use - would be going up.

Martin Lewis's explanation of it can be read here...

Here's what you said...

Are there any regulations for energy supplies regarding the standing charge? Every time the unit price drops my supplier raises the standing charge. SianW

Our energy bills have dropped, now the heating is off. However, the high daily standing charge means my bills are off the starting blocks even before the switches are flicked. Come the winter the price cap will rise again - not unlike profiteering in wartime. Porthy

My standing charges are almost three times what they used to be. I've cut back on my usage to the point I pay more a month in standing charges than I do usage so having the unit price drop makes little impact. P hunt

The energy companies have ripped us off for the last two years. The daily standing charge has to go. The shareholders have had real good dividends over the past few years, and therefore must pay for the people that can't pay their bills, because of the bonuses they have received. michael rogers

The Money blog is your place for consumer news, economic analysis and everything you need to know about the cost of living - bookmark news.sky.com/money.

It runs with live updates every weekday - while on Saturdays we scale back and offer you a selection of weekend reads.

Check them out this morning and we'll be back on Monday with rolling news and features.

The Money team is Emily Mee, Bhvishya Patel, Jess Sharp, Katie Williams, Brad Young and Ollie Cooper, with sub-editing by Isobel Souster. The blog is edited by Jimmy Rice.

An investigation has been launched into whether the biggest banking merger since the financial crisis could harm competition.

The Competition and Markets Authority announced the inquiry into Nationwide's £2.9bn takeover of rival Virgin Money this morning.

The move would bring together the fifth and sixth largest retail lenders, creating a combined group with around 24.5 million customers and nearly 700 branches.

It would spell the end of the Virgin Money brand, with Nationwide planning to rebrand the business within six years.

The CMA has invited interested parties to give their views on the deal, as it considers whether it could "result in a substantial lessening of competition" in the market.

Nationwide struck the takeover agreement in March, and last week a clear majority of 89% of Virgin Money shareholders voted in favour, helping to clear the path to complete.

The government has sold £1.24bn of its shares in NatWest, accelerating the process of private ownership.

The Treasury's shareholding in the high street bank has fallen by approximately 3.5 percentage points to 22.5%.

NatWest, formerly Royal Bank of Scotland, received multibillion-pound bailouts during the 2008 financial crisis, leaving the government with an 84% stake.

The government has been selling down its stake in the lender, with Chancellor Jeremy Hunt planning to sell all of its interest in the bank by 2025 or 2026 should the Conservatives be re-elected.

There was supposed to be a public share sale this summer, allowing individuals, not just institutional investors, to purchase stock, but the plans have been shelved due to the election.

In recent years, the sell-off has become more rapid. In 2018, the government owned 62% of the group, but by December of last year that was down to just under 38%.

In March, that fell below 30%, meaning the government was no longer classed as a controlling shareholder in the lender.

Earlier this year, NatWest wrote to shareholders asking them to support an increase in the amount of stock the bank could buy back from the government in a year, from just under 5% to 15%.

The establishment of Great British Energy is among the last remnants of the "green prosperity plan" devised and championed by Ed Miliband, the shadow secretary of state for energy security and net zero, three years ago.

The former Labour leader's vision was to spend £28bn per year in the first five years of an incoming Labour government on decarbonising the UK economy.

However, as the current leader Sir Keir Starmer recognised, the issue was swiftly weaponised by the Conservatives because all the money - as Mr Miliband himself had made clear - would have been borrowed.

More importantly, the plan did not survive contact with Rachel Reeves, the shadow chancellor, who has made fiscal responsibility her priority.

The £28bn-a-year spending pledge was watered down in February this year to one of £23.7bn over the life of the next parliament.

A sizeable chunk of that will be on Great British Energy, described by Mr Miliband as "a new publicly owned clean power company", which Labour has said will be initially capitalised at £8.3bn.

And, instead of the money being borrowed, Labour is now saying "it will be funded by asking the big oil and gas companies to pay their fair share through a proper windfall tax".

Read on here...

Edinburgh, Aberdeen and Dundee are joining Glasgow as cities with Low Emission Zones where motorists could face fines up to £480 if they don't comply.

The zones were introduced two years ago, but drivers were given a grace period before charges began.

In Dundee, the grace period ended today - in Edinburgh and Aberdeen it's tomorrow.

A non-compliant vehicle entering the zone can be charged £60, which doubles with each subsequent breach up to a maximum of £480.

If paid within 14 days, the initial fine will be halved to £30.

Despite the warning, only 55% of drivers in Scotland are confident they know where the zones are in operation, according to online marketplace Carwow.

Some 30% of Scottish motorists are not sure if they understand the rules and 24% are not sure if their vehicle is compliant.

"We therefore need to tackle the lack of understanding among motorists about Low Emission Zones in Scotland – where they are and which cars are compliant - because, without better knowledge, millions of drivers are at risk of being fined," said Sally Foote, chief commercial officer at Carwow.

The Low Emission Zones aim to discourage high-polluting vehicles from entering certain areas, just like those in English cities like Sheffield and Bristol.

Unlike English Clean Air Zones, Scottish LEZs apply to all types of vehicles except motorbikes and mopeds.

Non-compliant vehicles are not allowed into those zones whatsoever, unlike English LEZs, which apply a daily charge.

Ultra-low emission vehicles are automatically compliant, but others must conform to certain Euro emission ratings, which can be found in your V5C logbook - or you can check online.

Cars, vans, minibuses, taxis and private hire vehicles with a petrol engine must have at least a Euro 4 rating, while those with diesel engines should have a Euro 6.

Grants are available to people living within 20km of a LEZ who have no other choice but to sell or adapt their vehicles.

Hackers say they have stolen confidential information from all Santander staff and millions of customers, reports the BBC.

A gang going by the name of ShinyHunters posted an advert on a hacking forum claiming to be selling 30 million people's bank account details, six million account numbers and balances, 28 million credit card numbers and HR information for staff.

Earlier this month, the bank said data was accessed belonging to customers in Chile, Spain and Uruguay and all current Santander employees, but nothing that would allow transactions to take place.

As of March, Sandander as a whole employed more than 211,000 people and as of 30 June 2021, 20,900 employees worked for Santander UK.

Santander has declined to comment on the claims beyond a statement released on 14 May.

It read: "Certain information relating to customers of Santander Chile, Spain and Uruguay, as well as all current and some former Santander employees of the group had been accessed.

"No transactional data, nor any credentials that would allow transactions to take place on accounts are contained in the database, including online banking details and passwords. The bank's operations and systems are not affected, so customers can continue to transact securely.

"We apologise for the concern this will understandably cause and are proactively contacting affected customers and employees directly."

ShinyHunters have previously sold data stolen from AT&T and claim to be selling private data hacked from Ticketmaster, the BBC reported.

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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.

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May 27, 2024

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Spectator racism is still rife in Australia's major football codes—new research shows it may even be getting worse

by Keith Parry, Connor MacDonald, Daryl Adair and Jamie Cleland, The Conversation

The annual Indigenous rounds in the Australian Football League (AFL) and National Rugby League (NRL) celebrate Aboriginal and Torres Strait Islander cultures.

These events highlight the contributions of Indigenous players and aim to promote cultural awareness and foster reconciliation.

Some non-Indigenous sports fans, however, do not appreciate these initiatives. Some, in fact, continue to hurl bigoted abuse at players.

While many people would assume spectator racism is becoming rarer, our new study suggests the opposite is true among Australia's major male-dominated sporting codes.

Spectator racism may be getting worse

Some Australian football spectators use the stadium to vent hostile attitudes toward people of color, whether Indigenous, Pacific Islander, African or Asian.

This realization prompted us to conduct the first large-scale study of spectator racism in the three major men's leagues.

In 2021, we surveyed 2,047 participants from across the AFL, NRL and A-League Men, focusing on those who self-identified as white. We wanted to gather insights on racism as they witnessed and understood it while attending matches.

We found sobering evidence of the persistence of racism within these spectator communities, despite efforts by sports to combat it: 50% of AFL fans, 36% of NRL spectators and 27% of A-League Men fans had witnessed racist behavior during their lifetimes.

We asked respondents when they had witnessed racism and, as the table below shows, fans of all codes reported they had seen it at greater levels in the past two years compared to periods before this time.

This finding suggests fan racism is getting worse in all three sports and in the A-League Men, this reported racism is growing at the fastest rate of the three codes.

Acknowledging the problem

Spectator racism has long been an issue in Australian men's sports.

National sport governing bodies acknowledge there is a problem, but have for many years struggled to effectively combat it, either failing to respond resolutely or doing so too slowly .

In 2021, the Australian Human Rights Commission provided sports with guidelines for addressing spectator racism , and since then penalties for transgressions have become more consistent.

However, poor behavior from some fans has hardly disappeared.

Our new research, published in the International Review for the Sociology of Sport , found spectator racism continues to be present in three major Australian men's leagues: the AFL, NRL and A-League Men.

The impact on athletes

The impact of fan racism is brutal for players.

In recent years, Indigenous footballers Adam Goodes and Latrell Mitchell and Cody Walker have borne the brunt of vitriol like this.

By comparison, the A-League Men has featured few Indigenous players, but racism towards athletes from migrant backgrounds has certainly been obvious, along with neo-Nazi expressions of white supremacy.

Fan explanations for racism

Many survey respondents contended that spectator racism is learned behavior, passed down through families or like-minded fans. In that sense, racism is normalized, especially in public places like sports stadiums where barrackers may feel anonymous.

Most of those surveyed strongly criticized racial prejudice , acknowledging Australia's history of racism and ongoing examples of bigotry at sport events, with some pointing to even worse behavior among fans online via social media .

Some fans who opposed racism explained it as a moral failing of individuals, whom they perceived to be "bad apples." But by focusing solely on individuals, they overlooked wider social influences.

Racism is acquired behavior, not just a personal choice, and it arises via institutions such as sport and social practices like barracking at the footy.

Some respondents from our study were comfortable with "casual bigotry" whereby racist comments made in the "heat of the moment" are deemed "banter." They seemed unaware this permissive attitude allows racist discourses to remain alive.

A minority of respondents were unfazed by any of this, freely admitting their own racist views, declaring a belief that sports, and society, are best served by white power.

Sport's response to racism

In the football codes, there is now better awareness of what constitutes racist barracking at games. Greater media coverage of racist incidents, especially via its capture on digital devices, has improved the chance of offenders being exposed, along with potential consequences.

Just as importantly, the three football leagues have improved their detection measures, such as by anonymous reporting hotlines within stadiums. Indeed, our study showed most fans are aware of mechanisms to report racist (or other discriminatory) behavior.

Yet, despite a significant proportion of our survey respondents indicating they had observed inappropriate crowd conduct, just 3% of AFL fans, 2% of NRL fans, and 1% of A-League Men supporters reported using the hotlines.

So, there is a gap between some white fans witnessing and reporting racist incidents.

Therefore, while sports leagues have introduced penalties for racism, the effectiveness of these measures is limited by their reliance on witness responses and the complexity of observers providing proof.

What more can be done?

In the context of anti-racism and Australian society, the fight against bigotry must not be left to Aboriginal and Torres Strait Islander peoples and people from culturally diverse backgrounds.

Prime responsibility lies with white Australians who, after all, are generally privileged to not be objects of racial bigotry. Therefore, white sports fans who reject the ideology of white supremacy, like racist barracking at a game, have the opportunity to demonstrate a sense of solidarity with those who have been the subject of abuse.

It is often said education can alter racist attitudes. After all, if racism can be learned, surely it can be unlearned .

That process is certainly worth pursuing but in the short term, the imposition of consequences for inappropriate fan conduct is vital.

The football codes are finally getting serious about penalties, with lengthy or even life-time bans .

What is urgently needed, though, is a greater commitment by fans, especially white fans, to report racism when they observe it. Otherwise they're giving a free kick to bigots.

Provided by The Conversation

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Defining A Research Problem
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Formulating a Research Problem
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Research problem
Research Purpose

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Research Problem || Defining a research Problem || Research
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Identifying a Research Problem: A Step-by-Step Guide
A research problem is a specific issue, inconsistency, or gap in knowledge that needs to be addressed through scientific inquiry. It forms the foundation of a research study, guiding the research questions, methodology, and analysis. Why is identifying a research problem important?
The Research Problem/Question
A research problem is a definite or clear expression [statement] about an area of concern, a condition to be improved upon, a difficulty to be eliminated, or a troubling question that exists in scholarly literature, in theory, or within existing practice that points to a need for meaningful understanding and deliberate investigation.
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What is a Research Problem? Characteristics, Types, and Examples
A research problem is a gap in existing knowledge, a contradiction in an established theory, or a real-world challenge that a researcher aims to address in their research. It is at the heart of any scientific inquiry, directing the trajectory of an investigation. The statement of a problem orients the reader to the importance of the topic, sets ...
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Key Takeaways

Understanding the Essence of Identifying a Research Problem

Importance in Academic Research

Initial Steps to Identification

Exploring Sources for Research Problem Identification

Existing Theories and Frameworks

Consultation with Academic Mentors

Formulating the Research Problem

Setting Research Objectives

Determining Research Questions

Evaluating the Scope and Relevance of the Research Problem

Significance to the Field

Potential Impact on Existing Knowledge

Techniques for Refining the Research Problem

Incorporating Feedback

Iterative Refinement Process

Challenges in Identifying a Research Problem

Dealing with Ambiguity

Balancing Novelty and Practicality

Advanced Strategies for Identifying a Research Problem

Utilizing Technology and Data Analytics

Engaging with Industry and Community Needs

Frequently Asked Questions

Why is identifying a research problem important?

How do I identify a suitable research problem?

What are some common pitfalls in identifying a research problem?

Can technology help in identifying a research problem?

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Organizing Your Social Sciences Research Paper

Importance of...

Structure and Writing Style

Research Problem – Examples, Types and Guide

Research Problem

Types of Research Problems

Descriptive problems

Exploratory problems

Explanatory Problems

Predictive Problems

Evaluative Problems

How to Define a Research Problem

Components of a Research Problem

Research Problem Examples

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Environmental Science

Research Problem Example for Students

Applications of Research Problem

Purpose of Research Problems

Characteristics of Research Problem

Advantages of Research Problem

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Research Problem – Definition, Steps & Tips

Why is Research Problem Critical?

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Step 1: Identifying Problem Area – What is Research Problem

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Step 2: Understanding the Research Problem

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Particularity and Suitability

Example of a Specific Research Problem

Frequently Asked Questions

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