a critical research methodology

What is Critical Research? | Definition, Examples & Methods

Introduction

What does critical research mean, what is an example of critical qualitative research, approaches to critical theory.

Critical research was created out of a need to examine power , inequities, and the resulting societal implications on the status quo in society. It is a necessary departure from traditional scientific research in that it looks beyond what is directly observable to analyze the social world and develop social theory from novel perspectives to address previous injustices. In this article, we'll look at what critical theory entails for qualitative research , as well as the different strands that make up critical research.

In specific terms, critical research examines the nature of power dynamics influencing the social world. More broadly, this has implications for understanding inequality and disparity across cleavages of race, gender, ethnicity, sexual orientation, and economic class, among other differences in identity.

While there are many different strands to critical research, there are a number of common characteristics that are shared by scholars of critical theory:

Contextualization : Traditional research assumes a singular, almost absolutist approach to knowledge. In contrast, critical theory challenges the positivist outlook on scientific research and assumes a more sociocultural outlook to the social world. In adopting a more contextualized approach to any particular social phenomenon, scholars look to making propositions specific to different contexts rather than defining grand, unifying theories that explain socially constructed concepts regardless of individual or cultural circumstances.
Subjectivity : Unlike more positivist approaches to research, critical research presupposes a lack of an ability to directly observe physical reality. Moreover, a researcher's perception is often confounded by culturally-reinforced presumptions such as stereotypes and other biases that privilege those in power. The possibility that the social world can be subjectively construed directly challenges assumptions of a positivist understanding of social phenomena. Instead, critical research encourages scholars and laypeople alike to consider the world from different points of view in order to identify problems and inequities that are otherwise invisible within traditional worldviews.
Social change : Critical research is seldom interested in generating insights purely out of intellectual curiosity. Critical scholars tend to adopt a philosophy of social justice where research is aimed at benefiting marginalized or oppressed populations who lack the same opportunities and benefits that are otherwise granted to those in mainstream society. In this respect, research and analysis within a critical paradigm are merely preliminary steps in a process that appeals to institutions, stakeholders, and social activists to draw on actionable insights from the research and make tangible proposals for enacting change.
Transformation : Similar to the imperative of social change, transformation deals with fundamentally altering contemporary paradigms. However, this aspect to critical research is more concerned with problematizing traditional perspectives of the social world and the phenomena within it, both from a layperson's point of view and from the view of traditional academic institutions that perpetuate mainstream scientific inquiry. Rather than simply acknowledge the subjective nature of the social world, critical research calls for fundamentally transforming perceptions and attitudes in a manner that views marginalized populations more equitably.

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One of the more famous studies to produce a critical analysis is the doll test first devised by Mamie Clark, then conducted with husband Kenneth Clark starting in the 1940s and replicated in later years. In the doll test, children were asked how they felt about dolls that were put in front of them. The children preferred to play with the dolls that looked white rather than the dolls that looked black, and had more positive views about the white-looking dolls. Children who were black also tended to share the same perception of black-looking dolls, which suggested that their surrounding environment - particularly the school system but more broadly the culture around them - profoundly impacted them by reinforcing negative stereotypes about racial minorities.

Critical theorists argue that such stereotypes, especially when perpetuated by institutions like education and mass media, further contribute to economic and social disparities when children of color experience exposure to negative attitudes about race and ethnicity. This novel research provided fundamental insights that led to the following real-world changes:

Desegregation of schools : This research took place in the era where public schools in the United States were separated by race. The findings from the doll test helped make the case that institutionalized discrimination had effects on the educational and emotional development of children of color, ultimately leading to judicial rulings that contributed to school desegregation.
Educational reforms : Subsequent discussions of racial stereotypes have helped to further promote initiatives for racial equity and equality in public education. While still undoubtedly controversial to this day, efforts to promote diversity training for teachers, multicultural curriculum development, and other policies to address racial disparities can be partly attributed to the findings of the doll test.
Anti-discrimination policies : The findings from the doll test form a scientific basis for anti-discrimination frameworks for public policy, workplace organization, and other formal institutions. Where racism and equality might otherwise be abstract, potentially vague concepts, a scientific framework regarding discriminatory attitudes provides a language for discussing practical implications addressing racism.

Here are some of the various forms of critical research. Keep in mind that these approaches are not exclusive to each other, though they have their own distinct focus to shed light on specific issues relevant to the social sciences, nor are they exhaustive of the entire array of critical theory.

Critical discourse analysis : Researchers who critically analyze communication look at how people exercise power through speech to manipulate or control others. This analytical method connects theories from linguistics, sociology, and anthropology to look at the power of language in constructing social reality.
Critical ethnography : Ethnography is an all-encompassing approach to research aimed at capturing relationships, practices, and behaviors within any given context. Beyond a comprehensive examination of cultures, critical ethnographers use the resulting findings to advocate for social change.
Critical methodology : Critical scholars may also look at how methods are used to construct scholars' epistemology about scientific knowledge and question approaches to science that emphasize objectivity to a fault. Critical methodology advocates for reflexivity and participatory research as a departure from traditional research methods.
Critical race theory : Scholars engaged in critical race theory look at longstanding racial disparities to examine how institutions and power structures perpetuate racism and how people of color can challenge those structures from legal and advocacy standpoints in order to foster equity and equality.
Decolonizing research : Focusing on the critique that most established research comes from a Western-based perspective, research on decolonization seeks to deconstruct established philosophical paradigms that disadvantage perspectives of indigenous populations, cultures from the Global South, and other communities that have long been ignored by mainstream scholarship.

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Critical Research and Qualitative Methodologies: Theoretical Foundations and Contribution to Nursing Research

Affiliations.

1 Assistant Professor, Faculty of Nursing, Université de Montréal, Montréal, Canada [email protected].
2 Associate Professor, Department of Nursing, Université du Québec en Outaouais, Saint-Jérome, Québec, Canada.
PMID: 35584891
DOI: 10.1891/RTNP-2021-0014

Background: Methodological approaches that draw on critical perspectives (critical ethnography, critical phenomenology, and critical grounded theory) share common concepts, including social justice, reflexivity, positionality, pragmatism and social transformation. These approaches differ from conventional phenomenology, ethnography and grounded theory despite sharing common methodological grounds. Purpose: In this article, we will outline the major contributions of critical theory, as a research paradigm, to the development and evolution of qualitative methodologies. In particular, we will discuss their application to nursing research. The historical and conceptual underpinnings of these critical methodologies will first be described to highlight their paradigmatic characteristics and implications for nursing. Implications for Practice: Although not yet widely employed in nursing research, critical qualitative methodologies are particularly well suited to the discipline as they shed light on issues of power, social control, and marginalization among the vulnerable populations with whom nurses practise on a daily basis. The use of critical approaches can expose the epistemic injustice and social and health inequality that continue to prevail in our society.

Keywords: critical theory; ethnography; grounded theory; phenomenology; qualitative methods.

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Handbook of Critical Education Research

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This handbook offers a contemporary and comprehensive review of critical research theory and methodology. Showcasing the work of contemporary critical researchers who are harnessing and building on a variety of methodological tools, this volume extends beyond qualitative methodology to also include critical quantitative and mixed-methods approaches to research. The critical scholars contributing to this volume are influenced by a diverse range of education disciplines, and represent multiple countries and methodological backgrounds, making the handbook an essential resource for anyone doing critical scholarship. The book moves from the theoretical to the specific, examining various paradigms for engaging in critical scholarship, various methodologies for doing critical research, and the political, ethical, and practical issues that arise when working as a critical scholar. In addition to mapping the field, contributions synthesize literature, offer concrete examples, and explore relevant contexts, histories, assumptions, and current practices, ultimately fostering generative thinking that contributes to future methodological and theoretical breakthroughs. New as well as seasoned critical scholars will find within these pages exciting new ideas, challenging questions, and insights that spur the continuous evolution and grow the influence of critical research methods and theories in the education and human disciplines.

Chapter | 8 pages, introduction, chapter one | 87 pages, chapter 1 | 18 pages, critical education research, chapter 2 | 17 pages, the paradigm wars reconsidered, chapter 3 | 19 pages, critical approaches to quantitative research, chapter 4 | 21 pages, black in time, chapter two | 133 pages, chapter 5 | 19 pages, education and colonialism, chapter 6 | 31 pages, the white supremacist core ontological architecture of western modernity, chapter 7 | 30 pages, queering critical educational research, chapter 8 | 17 pages, reflexivity 10.6 1, chapter 9 | 16 pages, the spatial logic of epistemic imaginaries, chapter 10 | 14 pages, where are the black folx, chapter three | 164 pages, chapter 11 | 19 pages, toward critical approaches to case study research, chapter 12 | 29 pages, critical ethnography in education research, chapter 13 | 26 pages, critical auto (-/) ethnography in everyday and educational research for social justice, chapter 14 | 19 pages, critical narrative inquiry, chapter 15 | 22 pages, a “good” university, chapter 16 | 21 pages, using critical discourse analysis to challenge and change educational practice and policy, chapter 17 | 18 pages, toward a critical history of education, chapter four | 72 pages, chapter 18 | 13 pages, (un)learning white supremacy ideologies to advance critical approaches to quantitative inquiry, chapter 19 | 16 pages, applied quantitative inquiry through a critical disability studies lens, chapter 20 | 22 pages, critical quantitative intersectionality, chapter 21 | 15 pages, what is the point, chapter five | 83 pages, chapter 22 | 16 pages, disrupting the binary, chapter 23 | 19 pages, critical networks in critical times, chapter 24 | 16 pages, critical space analysis, chapter 25 | 26 pages, multimodal inquiries inspired by post-philosophies, chapter six | 79 pages, chapter 26 | 14 pages, listening and learning through critical interviewing approaches in qualitative inquiry, chapter 27 | 17 pages, oral history as critique, chapter 28 | 22 pages, critical and feminist cartographies of observation, chapter 29 | 18 pages, critical survey research, chapter seven | 104 pages, chapter 30 | 18 pages, using qualitative data analysis software to help explore critical research questions, chapter 31 | 20 pages, shifting policy meanings, chapter 32 | 20 pages, the ethics and bureaucratization of data management, chapter 33 | 20 pages, advancing quantcrit in critical race spatial research, chapter 34 | 20 pages, beyond representation, chapter eight | 117 pages, chapter 35 | 20 pages, critical educational research and social movements, chapter 36 | 19 pages, “to whom are we accountable”, chapter 37 | 20 pages, families and educators co-designing, chapter 38 | 12 pages, validity as democratic deliberation, chapter 39 | 24 pages, topographies of research as relational, chapter 40 | 18 pages, institutional review boards.

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Critical Theory in Social Research: A Theoretical and Methodological Outlook

First Online: 27 October 2022

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Ashek Mahmud 4 &
Farhana Zaman 4

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Critical theory, a multidisciplinary and multifaceted approach, was put forward to reconstruct dominant ideology by the critical task of explaining and criticizing. Contextualizing this new approach, the chapter is designed to focus on the development of social thought and its application in social research grounding on the critical theory. The discussion, drawing from many kinds of literature, depicts that critical theory as a perspective of social praxis unveils the critical reality through a detailed analysis of leading texts, pervasive conversations, social interactions, and persistent social practices. Thereby, critical theory provides insight to form ‘Critical paradigm’ and ‘Critical Realist Paradigm’ that generates ‘Ideology critique’, ‘Critical action research’, and ‘Critical Discourse Analysis’ (CDA) as the dynamic research methods. With those, researchers can explain the relationship between theory and practice linking language, ideas and social actions. By highlighting the basic characteristics of critical theory, this chapter analyses its application in the field of social research focusing on when and in which context critical theory is applied. Finally, the chapter attempts to ascertain the emancipatory function of this new approach by providing some examples of research output in connection to perpetual social problems in modern social settings.

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Mahmud, A., Zaman, F. (2022). Critical Theory in Social Research: A Theoretical and Methodological Outlook. In: Islam, M.R., Khan, N.A., Baikady, R. (eds) Principles of Social Research Methodology. Springer, Singapore. https://doi.org/10.1007/978-981-19-5441-2_7

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The Four Types of Research Paradigms: A Comprehensive Guide

5-minute read

22nd January 2023

In this guide, you’ll learn all about the four research paradigms and how to choose the right one for your research.

Introduction to Research Paradigms

A paradigm is a system of beliefs, ideas, values, or habits that form the basis for a way of thinking about the world. Therefore, a research paradigm is an approach, model, or framework from which to conduct research. The research paradigm helps you to form a research philosophy, which in turn informs your research methodology.

Your research methodology is essentially the “how” of your research – how you design your study to not only accomplish your research’s aims and objectives but also to ensure your results are reliable and valid. Choosing the correct research paradigm is crucial because it provides a logical structure for conducting your research and improves the quality of your work, assuming it’s followed correctly.

Three Pillars: Ontology, Epistemology, and Methodology

Before we jump into the four types of research paradigms, we need to consider the three pillars of a research paradigm.

Ontology addresses the question, “What is reality?” It’s the study of being. This pillar is about finding out what you seek to research. What do you aim to examine?

Epistemology is the study of knowledge. It asks, “How is knowledge gathered and from what sources?”

Methodology involves the system in which you choose to investigate, measure, and analyze your research’s aims and objectives. It answers the “how” questions.

Let’s now take a look at the different research paradigms.

1. Positivist Research Paradigm

The positivist research paradigm assumes that there is one objective reality, and people can know this reality and accurately describe and explain it. Positivists rely on their observations through their senses to gain knowledge of their surroundings.

In this singular objective reality, researchers can compare their claims and ascertain the truth. This means researchers are limited to data collection and interpretations from an objective viewpoint. As a result, positivists usually use quantitative methodologies in their research (e.g., statistics, social surveys, and structured questionnaires).

This research paradigm is mostly used in natural sciences, physical sciences, or whenever large sample sizes are being used.

2. Interpretivist Research Paradigm

Interpretivists believe that different people in society experience and understand reality in different ways – while there may be only “one” reality, everyone interprets it according to their own view. They also believe that all research is influenced and shaped by researchers’ worldviews and theories.

As a result, interpretivists use qualitative methods and techniques to conduct their research. This includes interviews, focus groups, observations of a phenomenon, or collecting documentation on a phenomenon (e.g., newspaper articles, reports, or information from websites).

3. Critical Theory Research Paradigm

The critical theory paradigm asserts that social science can never be 100% objective or value-free. This paradigm is focused on enacting social change through scientific investigation. Critical theorists question knowledge and procedures and acknowledge how power is used (or abused) in the phenomena or systems they’re investigating.

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Researchers using this paradigm are more often than not aiming to create a more just, egalitarian society in which individual and collective freedoms are secure. Both quantitative and qualitative methods can be used with this paradigm.

4. Constructivist Research Paradigm

Constructivism asserts that reality is a construct of our minds ; therefore, reality is subjective. Constructivists believe that all knowledge comes from our experiences and reflections on those experiences and oppose the idea that there is a single methodology to generate knowledge.

This paradigm is mostly associated with qualitative research approaches due to its focus on experiences and subjectivity. The researcher focuses on participants’ experiences as well as their own.

Choosing the Right Research Paradigm for Your Study

Once you have a comprehensive understanding of each paradigm, you’re faced with a big question: which paradigm should you choose? The answer to this will set the course of your research and determine its success, findings, and results.

To start, you need to identify your research problem, research objectives , and hypothesis . This will help you to establish what you want to accomplish or understand from your research and the path you need to take to achieve this.

You can begin this process by asking yourself some questions:

What is the nature of your research problem (i.e., quantitative or qualitative)?
How can you acquire the knowledge you need and communicate it to others? For example, is this knowledge already available in other forms (e.g., documents) and do you need to gain it by gathering or observing other people’s experiences or by experiencing it personally?
What is the nature of the reality that you want to study? Is it objective or subjective?

Depending on the problem and objective, other questions may arise during this process that lead you to a suitable paradigm. Ultimately, you must be able to state, explain, and justify the research paradigm you select for your research and be prepared to include this in your dissertation’s methodology and design section.

Using Two Paradigms

If the nature of your research problem and objectives involves both quantitative and qualitative aspects, then you might consider using two paradigms or a mixed methods approach . In this, one paradigm is used to frame the qualitative aspects of the study and another for the quantitative aspects. This is acceptable, although you will be tasked with explaining your rationale for using both of these paradigms in your research.

Choosing the right research paradigm for your research can seem like an insurmountable task. It requires you to:

● Have a comprehensive understanding of the paradigms,

● Identify your research problem, objectives, and hypothesis, and

● Be able to state, explain, and justify the paradigm you select in your methodology and design section.

Although conducting your research and putting your dissertation together is no easy task, proofreading it can be! Our experts are here to make your writing shine. Your first 500 words are free !

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Critical Qualitative Research

Critical research serves to address societal structures and institutions that oppress and exclude so that transformative actions can be generated that reduce inequitable power conditions. We invite proposals for authored and edited volumes that describe critical social science research (re)conceptualizations, practices, and methodologies that can be used by other scholars who wish to design and implement critical qualitative inquiry. Critical Qualitative Research challenges modernist orientations toward research by using social theory, designs, and research practices that emerge from critical questions like: Who/what is heard? Who/what is silenced? Who is privileged? Who is disqualified? How are forms of inclusion/exclusion being created? How are relations of power constructed and managed? How do various forms of privilege and oppression intersect to impact life possibilities for various individuals and groups? How do the arts inform research? How can multiple knowledges be engaged in research? How can research be socially just?

Walking with Strangers

Mapping the Terrains of Student Voice Pedagogies

Whiteness Is the New South Africa

Politics, Pedagogy and Power

Re-Assembly Required

Representing Youth with Disability on Television

Conducting Hermeneutic Research

Place, Being, Resonance

Critically Researching Youth

Artistic Research Methodology

Key subject areas.

English Studies
German Studies
History & Political Science
Law, Economics & Management
Linguistics
Media & Communication
Romance Studies
Science, Society and Culture
Slavic Studies
Theology & Philosophy
Peter Lang Classics

Critical Thinking in Academic Research - Second Edition

(5 reviews)

Cindy Gruwell, University of West Florida

Robin Ewing, St. Cloud State University

Last Update: 2023

Publisher: Minnesota State Colleges and Universities

Language: English

Formats Available

Conditions of use.

Learn more about reviews.

Reviewed by Erin Weldon, Director of Instructional Design and Development, Trine University on 8/28/24

Comprehensiveness rating: 5 see less

The textbook offers a comprehensive overview of academic research with a focus on essential tools and strategies for researchers. It includes a valuable section on barriers of critical thinking. To enhance its utility, consider adding a section highlighting the advantages or benefits of critical thinking, which can help mitigate these barriers. While discussing challenges is crucial, perhaps positioning this section later in the textbook would allow readers to build a stronger foundation before addressing potential obstacles. A suggestion for the readers is to read the barriers chapter toward the end after you have a strong foundation of critical thinking in academic research.

Content Accuracy rating: 5

The textbook presents unbiased information and offers descriptive evidence to support its arguments on critical thinking topics. Examples illustrate the application of critical thinking in research. Throughout the text, valuable tips encourage readers to cultivate critical thinking skills and provide practical suggestions that they can put into action. For instance, in Chapter 5, learners are provided with tips on how to keep track of information. I appreciate the citation management software options. This is a great resource to get readers started on their research journey.

Relevance/Longevity rating: 5

The textbook effectively aligns with current research methods and strategies. The text includes the most recent academic trends. Its strategies provide learners with practical guidance on conducting thorough research, ensuring proper attribution and compliance with copyright regulations, which are increasingly important in today's world.

Clarity rating: 4

The textbook provides clear chapters that coincide with the purpose. I appreciate the examples to clarify the strategies for critical thinking in research. A few interactive quizzes could benefit from clearer instructions to enhance their effectiveness. For instance, in Chapter 8, providing specific guidance within the Main Concepts section would clarify the quiz's purpose. While the questions may appear factual, they actually require learners to identify the main concept or topic. This added clarity would improve the overall learning experience.

Consistency rating: 5

The textbook's topics are interconnected and progressively build upon one another, forming a comprehensive and reliable resource. The text begins by introducing key concepts of critical thinking, then progresses into effective research strategies, skills, and methodologies, concluding with a discussion of ethical considerations and standards for responsible research practices.

Modularity rating: 5

The text displays excellent readability. I appreciate the awareness of accessibility with the use of alt-text on the images. There should be little to no barriers for readers. To further enhance inclusivity, adding audio narration to the text would provide an alternative format that is easily accessible within the book.

Organization/Structure/Flow rating: 4

The overall organization of the textbook is clear and concise. See comment above about rearranging the barriers chapter later in the book such as after a section on the benefits as mentioned above.

Interface rating: 5

There does not appear to be any navigational issues throughout the book. From an accessibility standpoint, everything appears to be accessible in a way that would not distract or cause barriers to the reader.

Grammatical Errors rating: 5

No grammatical errors present or noticeable that I could see.

Cultural Relevance rating: 5

This comprehensive textbook fosters an inclusive learning environment by presenting a diverse range of examples that illustrate various perspectives. Readers are encouraged to develop a deep understanding of different cultures and experiences and appreciate the value of diverse viewpoints.

This text is an excellent resource for anyone who needs a textbook for a research class,. his comprehensive text serves as a valuable resource for students and researchers, providing a solid foundation for coursework in research methods.

Reviewed by Julie Jaszkowiak, Community Faculty, Metropolitan State University on 12/22/23

Organized in 11 parts, this his textbook includes introductory information about critical thinking and details about the academic research process. The basics of critical thinking related to doing academic research in Parts I and II. Parts III – XI provide specifics on various steps in doing academic research including details on finding and citing source material. There is a linked table of contents so the reader is able to jump to a specific section as needed. There is also a works cited page with information and links to works used for this textbook.

The content of this textbook is accurate and error free. It contains examples that demonstrate concepts from a variety of disciplines such as “hard science” or “popular culture” that assist in eliminating bias. The authors are librarians so it is clear that their experience as such leads to clear and unbiased content.

General concepts about critical thinking and academic research methodology is well defined and should not become obsolete. Specific content regarding use of citation tools and attribution structure may change but the links to various research sites allow for simple updates.

Clarity rating: 5

This textbook is written in a conversational manner that allows for a more personal interaction with the textbook. It is like the reader is having a conversation with a librarian. Each part has an introduction section that fully defines concepts and terms used for that part.

In addition to the written content, this textbook contains links to short quizzes at the end of each section. This is consistent throughout each part. Embedded links to additional information are included as necessary.

Modularity rating: 4

This textbook is arranged in 11 modular parts with each part having multiple sections. All of these are linked so a reader can go to a distinct part or section to find specific information. There are some links that refer back to previous sections in the document. It can be challenging to return to where you were once you have jumped to a different section.

Organization/Structure/Flow rating: 5

There is clear definition as to what information is contained within each of the parts and subsequent sections. The textbook follows the logical flow of the process of researching and writing a research paper.

Interface rating: 4

The pictures have alternative text that appears when you hover over the text. There is one picture on page 102 that is a link to where the downloaded picture is from. The pictures are clear and supportive of the text for a visual learner. All the links work and go to either the correct area of the textbook or to a valid website. If you are going to use the embedded links to go to other sections of the textbook you need to keep track of where you are as it can sometimes get confusing as to where you went based on clicking links.

Grammatical Errors rating: 4

This is not really a grammatical error but I did notice on some of the quizzes if you misspelled a work for fill in the blank it was incorrect. It was also sometimes challenging to come up with the correct word for the fill in the blanks.

There are no examples or text that are culturally insensitive or offensive. The examples are general and would be applicable to a variety of students study many different academic subjects. There are references and information to many research tools from traditional such as checking out books and articles from the library to more current such as blogs and other electronic sources. This information appeals to a wide expanse of student populations.

I really enjoyed the quizzes at the end of each section. It is very beneficial to test your knowledge and comprehension of what you just read. Often I had to return and reread the content more critically based on my quiz results! They are just the right length to not disrupt the overall reading of the textbook and cover the important content and learning objectives.

Reviewed by Sara Stigberg, Adjunct Reference Librarian, Truman College, City Colleges of Chicago on 3/15/23

Critical Thinking in Academic Research thoroughly covers the basics of academic research for undergraduates, including well-guided deeper dives into relevant areas. The authors root their introduction to academic research principles and practices in the Western philosophical tradition, focused on developing students' critical thinking skills and habits around inquiry, rationales, and frameworks for research.

This text conforms to the principles and frames of the Framework for Information Literacy for Higher Education, published by the Association of College and Research Libraries. It includes excellent, clear, step-by-step guides to help students understand rationales and techniques for academic research.

Essential for our current information climate, the authors present relevant information for students who may be new to academic research, in ways and with content that is not too broad or too narrow, or likely to change drastically in the near future.

The authors use clear and well-considered language and explanations of ideas and terms, contextualizing the scholarly research process and tools in a relatable manner. As mentioned earlier, this text includes excellent step-by-step guides, as well as illustrations, visualizations, and videos to instruct students in conducting academic research.

(4.75) The terminology and framework of this text are consistent. Early discussions of critical thinking skills are tied in to content in later chapters, with regard to selecting different types of sources and search tools, as well as rationales for choosing various formats of source references. Consciously making the theme of critical thinking as applied to the stages of academic research more explicit and frequent within the text would further strengthen it, however.

Chapters are divided in a logical, progressive manner throughout the text. The use of embedded links to further readings and some other relevant sections of the text are an excellent way of providing references and further online information, without overwhelming or side-tracking the reader.

Topics in the text are organized in logical, progressive order, transitioning cleanly from one focus to the next. Each chapter begins with a helpful outline of topics that will be covered within it.

There are no technical issues with the interface for this text. Interactive learning tools such as the many self-checks and short quizzes that are included throughout the text are a great bonus for reinforcing student learning, and the easily-accessible table of contents was very helpful. There are some slight inconsistencies across chapters, however, relative to formatting images and text and spacing, and an image was missing in the section on Narrowing a Topic. Justifying copy rather than aligning-left would prevent hyphenation, making the text more streamlined.

(4.75) A few minor punctuation errors are present.

The authors of this text use culturally-relevant examples and inclusive language. The chapter on Barriers to Critical Thinking works directly to break down bias and preconceived notions.

Overall, Critical Thinking in Academic Research is an excellent general textbook for teaching the whys and hows of academic research to undergraduates. A discussion of annotated bibliographies would be a great addition for future editions of the text. ---- (As an aside for the authors, I am curious if the anonymous data from the self-checks and quizzes is being collected and analyzed for assessment purposes. I'm sure it would be interesting!)

Reviewed by Ann Bell-Pfeifer, Program Director/ Instructor, Minnesota State Community and Technical College on 2/15/23

The book has in depth coverage of academic research. A formal glossary and index were not included. read more

Comprehensiveness rating: 4 see less

The book has in depth coverage of academic research. A formal glossary and index were not included.

The book appears error free and factual.

The content is current and would support students who are pursuing writing academic research papers.

Excellent explanations for specific terms were included throughout the text.

The text is easy to follow with a standardized format and structure.

The text contains headings and topics in each section.

It is easy to follow the format and review each section.

The associated links were useful and not distracting.

No evidence of grammatical errors were found in the book.

The book is inclusive.

The book was informative, easy to follow, and sequential allowing the reader to digest each section before moving into another.

Reviewed by Jenny Inker, Assistant Professor, Virginia Commonwealth University on 8/23/22

This book provides a comprehensive yet easily comprehensible introduction to critical thinking in academic research. The author lays a foundation with an introduction to the concepts of critical thinking and analyzing and making arguments, and then moves into the details of developing research questions and identifying and appropriately using research sources. There are many wonderful links to other open access publications for those who wish to read more or go deeper.

The content of the book appears to be accurate and free of bias.

The examples used throughout the book are relevant and up-to-date, making it easy to see how to apply the concepts in real life.

The text is very accessibly written and the content is presented in a simple, yet powerful way that helps the reader grasp the concepts easily. There are many short, interactive exercises scattered throughout each chapter of the book so that the reader can test their own knowledge as they go along. It would be even better if the author had provided some simple feedback explaining why quiz answers are correct or incorrect in order to bolster learning, but this is a very minor point and the interactive exercises still work well without this.

The book appears consistent throughout with regard to use of terminology and tone of writing. The basic concepts introduced in the early chapters are used consistently throughout the later chapters.

This book has been wonderfully designed into bite sized chunks that do not overwhelm the reader. This is perhaps its best feature, as this encourages the reader to take in a bit of information, digest it, check their understanding of it, and then move on to the next concept. I loved this!

The book is organized in a manner that introduces the basic architecture of critical thinking first, and then moves on to apply it to the subject of academic research. While the entire book would be helpful for college students (undergraduates particularly), the earlier chapters on critical thinking and argumentation also stand well on their own and would be of great utility to students in general.

This book was extremely easy to navigate with a clear, drop down list of chapters and subheadings on the left side of the screen. When the reader clicks on links to additional material, these open up in a new tab which keeps things clear and organized. Images and charts were clear and the overall organization is very easy to follow.

I came across no grammatical errors in the text.

Cultural Relevance rating: 4

This is perhaps an area where the book could do a little more. I did not come across anything that seemed culturally insensitive or offensive but on the other hand, the book might have taken more opportunities to represent a greater diversity of races, ethnicities, and backgrounds.

This book seems tailor made for undergraduate college students and I would highly recommend it. I think it has some use for graduate students as well, although some of the examples are perhaps little basic for this purpose. As well as using this book to guide students on doing academic research, I think it could also be used as a very helpful introduction to the concept of critical thinking by focusing solely on chapters 1-4.

Introduction
Part I. What is Critical Thinking?
Part II. Barriers to Critical Thinking
Part III. Analyzing Arguments
Part IV. Making an Argument
Part V. Research Questions
Part VI. Sources and Information Needs
Part VII. Types of Sources
Part VIII. Precision Searching
Part IX. Evaluating Sources
Part X. Ethical Use and Citing Sources
Part XI. Copyright Basics
Works Cited
About the Authors

Ancillary Material

About the book.

Critical Thinking in Academic Research - 2nd Edition provides examples and easy-to-understand explanations to equip students with the skills to develop research questions, evaluate and choose the right sources, search for information, and understand arguments. This 2nd Edition includes new content based on student feedback as well as additional interactive elements throughout the text.

About the Contributors

Cindy Gruwell is an Assistant Librarian/Coordinator of Scholarly Communication at the University of West Florida. She is the library liaison to the department of biology and the College of Health which has extensive nursing programs, public health, health administration, movement, and medical laboratory sciences. In addition to supporting health sciences faculty, she oversees the Argo IRCommons (Institutional Repository) and provides scholarly communication services to faculty across campus. Cindy graduated with her BA (history) and MLS from the University of California, Los Angeles and has a Masters in Education from Bemidji State University. Cindy’s research interests include academic research support, publishing, and teaching.

Robin Ewing is a Professor/Collections Librarian at St. Cloud State University. Robin is the liaison to the College of Education and Learning Design. She oversees content selection for the Library’s collections. Robin graduated with her BBA (Management) and MLIS from the University of Oklahoma. She also has a Masters of Arts in Teaching from Bemidji State University. Robin’s research interests include collection analysis, assessment, and online teaching.

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GEOG 410 - Research Methodology

Verifying If An Article Is Peer-Reviewed
Should I Trust Internet Sources?
Suggested Databases for Finding Sources
Critical Analysis
Creating an Annotated Bibliography
Creating a Literature Review
Resources for Writing Research Proposals
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Introduction

Critical analysis may or may not be a component of this particular course's evaluation, but it is an important component of any research process.

Inquiry-based learning

Critical thinking is at the heart of scientific inquiry. A good scientist is one who never stops asking why things happen, or how things happen. Science makes progress when we find data that contradicts our current scientific ideas.

Scientific inquiry includes three key areas:

1. Identifying a problem and asking questions about that problem 2. Selecting information to respond to the problem and evaluating it 3. Drawing conclusions from the evidence

Hart, T. (2018, 18 October) Teaching critical thinking in science - the key to students' future success. Brighter Thinking Blog . https://www.cambridge.org/us/education/blog/2018/10/18/teaching-critical-thinking-science-key-students-future-success/

Writing Critical Analysis Papers

Links and tips on how to conduct a critical analysis

Critical Thinking & the Scientific Method "Critical thinking involves constantly asking questions, examining information and evidence, and figuring out conclusions. All of these actions are the basis for the scientific method, which then gives good evidence on which to base conclusions."
How to Write a Critical Analysis (with examples and tips) "Critical analysis is the detailed examination and evaluation of another person's ideas or work. It is subjective writing as it expresses your interpretation and analysis of the work by breaking down and studying its parts... Good critical analysis evaluates the ideas or work in a balanced way that highlights its positive and negative qualities."
CQ Researcher Online This link opens in a new window Addresses controversial topics in a balanced, unbiased manner, with regular reports on topics in health, international affairs, education, the environment, technology and the U.S. economy.

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ISBN: 9798888903469

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— Blackwell's
— Waterstones

While all oppressions are equal, some are more equal than others.

This statement, borrowed from George Orwell's Animal Farm and written and marinated to fit within and without our call for ethical research, helps us to see how contemporary research processes are singular and fail to account for the complex histories, realities and values of marginalized communities. Such a failure to account and re/member has had massive symbolic and material consequences on marginalized communities, illustrated by the number of deaths we continue to witness everyday. Those deaths have been sanctioned and authorized by the ways in which we come to know what we know and how that is imprinted in our policies and everyday existence. This book looks at knowledge production as a process of giving an account of those losses, in ways that help knowledge production to be a mechanism of remembering (cognitive) and re/membering (communi/ity or bring together/solidarity/ a form of epistemological and ontological demonstration).

Ethical knowledge production becomes a process of relationship that remembers the histories, values and realities of people in ways that are transformative and political. Such an expression fails to arrive at an end, and rather recognizes knowledge production as endless production of knowledge. Such a process goes against the neoliberal mechanism of commodifying knowledge for sale in the market.

This edited collection attempts to engage with current qualitative research methodologies and approaches from a critically and ethically reflexive standpoint. Critical Reflexive Research Methodologies seeks to unravel colonial practices that continue to hide within qualitative approaches in ways that invite a new reimagining of working within and without qualitative method/ologies. The collection therefore seeks to bring to the fore the lived experiences of the studied to their storied life in ways that are ethically and politically congruent. This work therefore seeks to bring forth Foucault's subterranean narratives steeped in contexts and experiences that can critically invert the dominant (colonial, capitalist, state) practices in existing research.

Part of the Studies in Critical Social Sciences series

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Article Contents

Introduction, materials and methods, supplementary material, author contributions, deviations from the preregistration, data availability.

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Selective insensitivity to income held by the richest

Competing Interest: The authors declare no competing interests.

Article contents
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Supplementary Data

Barnabas Szaszi, Hooman Habibnia, Josephine Tan, Oliver P Hauser, Jon M Jachimowicz, Selective insensitivity to income held by the richest, PNAS Nexus , Volume 3, Issue 9, September 2024, pgae333, https://doi.org/10.1093/pnasnexus/pgae333

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The misperception of income inequality is often touted as a critical barrier to more widespread support of redistributive policies. Here, we examine to what extent and why (mis)perceptions vary systematically across the income distribution. Drawing on data from four studies ( N = 2,744)—including a representative sample and preregistered incentive-compatible experiments—we offer converging evidence that people specifically underestimate the amount of income held by the top of the income distribution. While this selective underestimation is likely driven by multiple mechanisms, including systemic factors, we find that cognitive biases contribute to the observed pattern of results. The rise of inequality in many developed countries has been documented before, and the fact that this growing inequality is largely driven by the outsized gains of the richest individuals may pose new challenges previously underappreciated: our theory and findings highlight that cognitive biases pose a key obstacle to people's recognition of the concentration of income among the richest individuals, and may potentially distort their preferences for redistribution. We conclude by discussing future directions for research and the importance of incorporating behavioral and cognitive limitations into the design of redistributive public policy.

Across four studies, we show that people uniquely underestimate incomes concentrated at the upper end of the income distribution, leading to a systematic underestimation of inequality. With inequality's rise being largely driven by the outsized gains of the richest, this selective underestimation may contribute to people's lower support for redistribution. We find that this underestimation is partially driven by cognitive biases, suggesting correcting people's perceptions about the income of the richest may be challenging. Finally, our findings indicate that inequality should not be treated equally across the income distribution. Beyond summary measures of inequality such as the Gini coefficient, research and policy may need to shift toward being more sensitive to where inequality is concentrated.

While within-country economic inequality has risen around many parts of the world in recent decades, its growth in many developed countries is often driven by those at the very top of the income distribution ( 1–3 ). For instance, in the United States, between 1980 and 2020, the share of incomes held by the top 1% nearly doubled from 10 to 19%, while the top 10%'s income share—excluding the top 1%—increased far more modestly, from 24 to 27% ( 3 ). Critically, as inequality rose, the fraction of people supporting redistribution in the United States showed no significant increase since the 1970s ( 4–7 ).

Prior research suggests that to redress inequality and garner support for redistribution, people may need to recognize the existence and degree of inequality, particularly its growth at the very top. However, the perception of inequality often does not match reality ( 8–13 ), with some studies finding evidence for underestimation (e.g. 8 , 14 , 15 ), while others show support for overestimation of inequality (e.g. 11 , 16 ). In the current research, we focus on the top of the income distribution—given their outsized gains over the last few decades—and examine whether (and why) the perceptions of the incomes of this group in particular are commonly misperceived, and discuss the policy consequences of our findings.

Theories across the social sciences make competing predictions about the perception of incomes at the very top of the income distribution. For instance, the upward social comparison hypothesis ( 17 ) suggests that people are more prone to making upward than downward social comparisons. That is, people are hypothesized to be more likely to pay attention to information about individuals richer than them than poorer than them, which may lead to greater accuracy for estimates of the top of the income distribution. Similarly, the richest individuals—being the most successful in economic terms—are often overrepresented in the media. As the media influences peoples’ perceptions more broadly ( 18 ), such overrepresentation can provide an important source of information in people's judgments of inequality and perhaps contribute to a more accurate perception of the resources held by the richest ( 10 ).

In contrast, other theories predict lower overall accuracy at the upper end of the income distribution. The network hypothesis suggests that because people are often geographically segregated by income and wealth, many of them rarely interact with those from other social classes, particularly with individuals from the top of the income distribution ( 19–21 ). Because people's perceptions of incomes are shaped by personal experience ( 22 ) including their ideology ( 23 ), this perspective suggests they may underestimate the incomes of the richest individuals. In addition to geographical segregation, theories on cognitive biases also shed light on why people commonly underestimate the incomes of the very top of the income distribution (see also 24 , 25 ). Scope insensitivity refers to people's tendency to be insensitive to the quantity of objects, such that an additional unit is perceived and valued less than the previous one ( 26 ). Because scope insensitivity has been documented across several domains—including visual and auditory perception, social psychology, and economics ( 27–30 )—it may also occur in the domain of income estimations.

In sum, there are several potential mechanisms—both systemic and cognitive—that may shape how people perceive incomes by the upper echelons of the income distribution, but it is unclear how or when this occurs. Consequently, in the present research, we examine whether people over- or underestimate incomes at the upper end of the income distribution, and whether this effect is unique to this part of the distribution. In addition, we examine potential underlying mechanisms of the observed pattern of results. To do so, we combined several complementary methods and data. First, we conducted a preregistered cross-sectional study, as well as a replication with an incentivized US sample, which found that people strongly and consistently underestimate the resources of the top 1%—but this underestimation does not equally extend to other, lower income percentiles. Next, we conducted two preregistered and incentive-compatible experiments where we systematically manipulated income distributions. In these studies, we replicate our findings—i.e. participants were largely insensitive to changes in incomes of the top 1%—and show that this effect is unique to the top of the income distribution. Additional data from these experiments further suggest that cognitive processes in part contribute to the observed findings; more precisely, while our data are largely consistent with the predictions of scope insensitivity, it is likely that several factors—including both cognitive and systemic elements—influence people's judgments about inequality pertaining to the richest individuals in particular.

Study 1a: cross-sectional study

In Study 1a, we aimed to test whether people under- or overestimate the amount of income held by the top of the income distribution and explore whether this misperception is unique to this group. 990 US residents (52.9% female, M age = 44.27 years) recruited from luc.id completed the study online. Those who successfully completed the attention check were provided with an explanation of income percentiles. Next, participants were asked to self-report the US county they currently live in and then estimated the minimum annual household income thresholds of the 10th, 20th, 30th, 40th, 50th, 60th, 70th, 80th, 90th, 95th, and 99th percentiles of this county. a We subsequently calculated how much perceived income thresholds differed from the objective income thresholds in each county, and in each percentile, which we calculated using data provided by the Economic Policy Institute ( 31 , 32 ). Using Wilcoxon’s tests clustered by participants, we found that participants underestimated the income thresholds of the top 1% ( P < 0.001, Z = 12.490, r = 0.513), but this underestimation did not equally extend to lower percentiles (see Figure 1 , top panel; see also Table S1 ). For example, people underestimated the income threshold of the top 1% more so than that of the top 5% ( P < 0.001, Z = 13.465, r = 0.553). Detailed results and robustness checks for this and all subsequent studies are reported in the Supplementary Materials .

The difference between participant estimates of income average per quintile and the actual income average per quintile in Study 1a (top panel) and Study 1b (bottom panel). Note that data for Figure 2 are specific to responses from only the top 1% treatment condition. As this figure shows, participants underestimated incomes held by the top 1%, but were relatively accurate—and if anything, somewhat overestimated—incomes held by the bottom 80% of this fictional society.

Study 1b: preregistered replication in an incentivized US sample

In Study 1b, we conducted a preregistered replication of Study 1a and financially incentivized accurate responding. The preregistration is available at https://aspredicted.org/RPG_SC7 . We obtained a sample aimed to be representative by gender and race, as filtered by Prolific. 834 US citizens ( M age = 37.83, 49.1% female) completed the study online. The procedure of the study was identical to Study 1a with one key difference. Participants were told that they would earn an additional bonus payment of $0.50 if they completed one version of the so-called Bourdon test successfully, a task in which participants were asked to count the amount of “2”s present in a large table consisting of numbers. Participants who provided relatively accurate estimates (±5 from the real value) earned the bonus payment and could continue with the survey. Afterward, participants were informed that they could use this earned money to bet on their future performance in estimating income distributions, and if they were within the top 25% of all participants regarding the accuracy of the estimations, they would earn four times the amount of money wagered. 74% of the participants wagered some money (median amount wagered = $0.25).

Using identical means to Study 1a, we calculated how much perceived income thresholds differed from objective income thresholds in each percentile. Our results showed the same pattern of results as before: participants underestimated the income thresholds of the top 1% ( P < 0.001, Z = 7.520, r = 0.282), but this underestimation was selective, i.e. it did not equally extend to lower income percentiles (see Figure 1 , bottom panel; see also Table S3 ). Note that these results are identical when looking only at participants who wagered all their bonus money (24.33%) as well as participants who did not wager money at all (25.60%). These results suggest that participants were unable to provide more accurate guesses simply by trying harder. In additional supplementary analyses, we also find that these effects are not significantly moderated by political orientation.

Taken together, in Studies 1a and 1b, we found robust evidence across two cross-sectional studies from the United States that people systematically underestimate income of the top 1% and that this effect dissipates as we descend the income distribution. To further evidence the robustness of our findings, we aimed to replicate these results in Studies 2a and 2b using experimental methods. This approach also allows us to examine whether and how cognitive biases contribute to this misperception, beyond potential systemic factors.

Studies 2a and 2b: preregistered lab experiments with incentivized US sample

In Studies 2a and 2b, we developed an experimental design that allowed us to systematically manipulate the shape of the income distribution. After responding to the consent form, participants were asked to review the incomes of 100 individuals from a fictional society. Participants were required to click on the picture of each individual in any order of their choice, after which the income of the given individual appeared on the screen for 1.5 seconds. After finishing this task, participants were asked to assess the average income for each quintile of the income distribution of this fictional society and were offered an additional $0.50 bonus if their answers were within the top 25% accuracy among all participants. Participants subsequently repeated the same procedure for another fictional society.

We used a mixed within–between-participants design, where each participant saw two fictional societies in random order, one representing a control condition and the other representing a treatment condition (in Study 2a, only the top 1% treatment ; in Study 2b, either the top 1% treatment or top 10% treatment ). In the control condition, the distribution of the presented 100 incomes was broadly representative of the United States with respect to the mean and the percentage of people belonging to different income groups. The exact distributions are available in the Supplementary Materials . In the top 1% treatment condition , we used the same distribution as in the control group up until the richest individual, whose income was significantly increased. That is, the incomes of 99 individuals were the same between the control condition and the top 1% condition , and the only difference was the income of the richest person. In the top 10% condition , we used the same distribution as in the control group for the bottom 90 individuals and for the richest individual, but significantly increased the income of the richest 2–10% of individuals. That is, the incomes of 91 individuals were the same between the control and the top 10% condition , and the only difference was the increased income of the richest 2–10% of individuals. After participants viewed each fictional society, they were asked to estimate their perception of the income distribution—consistent with Eriksson and Simpson ( 33 )—separately for each quintile, as follows: What do you think is the average income of the richest/second/middle/fourth/poorest 20% of the individuals in the presented society? Note that in asking about income quintiles , we also intended to reduce the likelihood that experimenter demand effects would drive our results ( 34 ).

The aim of Study 2a was to test whether individuals were sensitive to variations in the incomes held by the top 1%. Accordingly, each participant in the study viewed two fictional societies in random order, one representing the control group and the other the top 1% treatment condition. In the top 1% treatment condition , we randomly varied between-participants the income of the richest earner to be either 35, 40, 45, or 50% of total income. We recruited participants via Prolific, and a total of 455 passed the attention check and completed the study (48.6% female, M age = 36.44 years). The preregistration of this study is available at https://aspredicted.org/MYF_KNM .

First, we compared participants’ perceptions of each income quintile to objective data. To do so, we collapsed data from participants’ responses in both fictional societies ( control and top 1% treatment groups) and used a clustered Wilcoxon signed-rank test clustered by participants to compare the differences in participants’ perceptions of each income quintile with objective data for each income quintile. In line with our prior studies, we find that participants underestimated the average income of the top 20% ( P < 0.001, Z = 7.870, r = 0.297), while they did not underestimate—and in fact, often overestimated—incomes of all other, lower quintiles (see the top panel of Figure 2 and Table S18 ).

(In)accuracy of participant's estimations of income thresholds by income percentile. Top panel reflects data from Study 2a, and bottom panel reflects data from Study 2b. Across both studies, we find that participants underestimated the income thresholds of the top 1% more so than all other percentiles.

Second, we compared participants’ estimated difference between the control and top 1% treatment conditions to the objective difference between the conditions with respect to the top quintile income. Our analyses revealed that the perceived difference ( Mdn = 50,000, P < 0.001, Z = −8.212, r = 0.385) in top quintile incomes between the control and top 1% treatment conditions was significantly smaller than the objective difference ( Mdn = 253,965). That is, participants somewhat but insufficiently incorporated the income change of the top 1%.

Finally, we tested how sensitive participants were to changes to the income of the richest individual in the top 1% treatment condition. Recall that the incomes of the richest person in the top 1% treatment varied between-person, ranging from 35, 40, 45, or 50% of total income. In comparing perceptions of average incomes of the richest quintile, we can test how sensitive participants are to different income levels of the richest person in the fictional society. We tested whether participants’ estimate of the richest quintile varied as a function of how rich the richest person was, and did not find a statistically significant effect ( F (3,451) = 1.084, P = 0.355; see also comparisons within top 20% quintile in the top panel of Figure 2 ).

Critically, it is unlikely that this effect is entirely driven by inattention to the income of the top 1% alone. Consider that participants were required to click on all individuals’ faces and observe their income one by one. In addition, we observe some difference in participants’ estimates of top income quintiles; when comparing the lowest (35% of total income) and highest (50% of total income) amounts of incomes held by the richest person in this fictional society, we find a small difference in perceptions (of 0.04%) which stands in contrast to the objective difference (of 8%). The detailed results of these additional analyses are reported in the Supplementary Materials .

In sum, in Study 2a, we replicated our earlier findings, showing that participants selectively underestimate at the top of the income distribution, and are not sufficiently sensitive to changes in the income of the top 1%. This study also provided evidence that this underestimation can occur even in the absence of systemic factors, suggesting that cognitive processes may also play a role—a possibility we investigate in more detail next.

In Study 2b, we aimed to accomplish three objectives: first, to replicate the findings from Study 2a; second, to provide evidence in an experimental setting that the effect does not equally extend to lower echelons of the income distribution (i.e. the underestimations is smaller for the top 10% than for the top 1%); and third, to test whether—in line with predictions from scope insensitivity theory—participants’ affective response does not proportionally vary with differences in the amount of income.

To accomplish these aims, we made two changes to Study 2a. First, in addition to the control condition, participants were randomly assigned to one of two treatment conditions, either the top 1% treatment condition where the income of the richest individual was increased to have 35% of the total income, or the top 10% treatment condition where the incomes of the top 2–10% of richest individuals were increased to altogether have 35% of the total income. The rank order of the individuals remained the same even after the increase of the incomes of the top 2–10%. Second, at the end of the study, we adapted measures from the scope insensitivity literature to capture participants’ affective responses to varying income levels ( 28 ). Each participant was shown 12 quasi-randomly generated incomes in random order, of which ten incomes corresponded to one of ten income brackets within the 50th–99th percentiles, one to the income of the richest person in the control condition, and one to the income of the richest person in the top 1% treatment condition. Participants were asked to indicate their feelings (i) toward an individual with such income and (ii) when imagining an income of that amount, rating the intensity of their feelings on a sliding scale ranging from 0 (“it has little emotional effect on me”) to 100 (“I have very intense feelings”). Following our preregistration, we created an individual-level affective response score at each level of income by averaging participants’ responses to these two items. The preregistration of Study 3b is available at https://aspredicted.org/57N_RWP .

We recruited participants via Prolific. 465 respondents (50.3% female, M age = 38.06 years) passed the attention check and completed the study. Replicating our earlier studies, we found that participants in the top 1% treatment condition underestimated the average income of the top 20% ( P < 0.001, Z = −6.004, r = 0.404). However, we did not find evidence in support of underestimation for participants in the top 10% treatment condition (in fact, if anything, they overestimated these incomes; P < 0.001, Z = 3.661, r = 0.233). This pattern of results suggests that the underestimation of incomes held by the richest is unique to the top of income distribution. These findings hold subject to a number of robustness checks, detailed in the Supplementary Materials .

Next, we tested participants’ affective responses to the 12 quasi-randomly generated incomes. Following our preregistration, we aggregated all responses to each level of income and subsequently plotted affective responses against absolute incomes, displayed in Figure 3 . At lower absolute income levels, we find that an increase from $58,000 to roughly twice that to $121,000 is associated with a 13.9-point increase in affective response (rated on a scale of 1–100). At the top of the income distribution, however, a nearly similar increase in affective response—13.7-point increase—occurs when moving from $593,000 to more than six times that to $3,589,000. That is, as income levels increase, participants’ affective response does not proportionally vary in response to differences in income (see also Supplementary Materials ). As these findings show, participants are less sensitive to changes in incomes as absolute incomes numbers become greater, consistent with scope insensitivity.

Participants’ affective response to incomes at varying levels from Study 2b. As incomes (solid line) increase, participants’ affective response (dashed line) does not increase commensurately—in line with predictions from scope insensitivity—providing suggestive evidence that this in part underlies the underestimation of the top 1% of income shares.

The current research sought to examine whether people are uniquely insensitive to the incomes of individuals at the upper end of the income distribution. Studies 1a and 1b provided correlational support, including by incentivizing accurate responses, that respondents systematically underestimate incomes of the top 1% of the income distribution. Indeed, this insensitivity was a defining feature of the top of the income distribution but did not extend consistently and commensurably to other income percentiles. In Studies 2a and 2b, we replicated these findings in an experimental setting, finding that this selective underestimation emerges even in the absence of systemic factors, suggesting the role cognitive processes may play in contributing to this misperception. Note that while prior research finds that participants often misperceive the level of inequality in society ( 8–12 )—sometimes finding evidence in support of underestimation ( 8 , 14 , 15 ) and at other times for overestimation ( 11 , 16 )—our studies provide converging evidence that participants selectively underestimate the amount of income held by the richest individuals in the population. However, our results are less clear on whether participants also misperceive incomes held by lower-income individuals. b , c Taken together, our findings suggest that people systematically underestimate the extent of inequality in society.

With inequality's rise in many developed countries being largely driven by the outsized gains of the richest individuals, our results suggest that the unique underestimation of the incomes held by the upper end of the income distribution may represent a significant barrier to action ( 37 , 38 ). Consider the corollary prediction that—because we find people to be insufficiently sensitive to inequality among the top 1%—their preferences for redistribution may also be less sensitive to changes among the concentration of incomes held by the top 1%. We tested this prediction in a supplementary study (SS1, see details in the Supplementary Materials ) using data from the International Social Survey Program ( 39 ), which asked participants to indicate their preferences for increased taxes on high-income individuals, reflective of support for redistribution ( 40 ). We examined whether changes in the actual concentration of incomes held by the top 1% between 1999 and 2009—obtained from the World Inequality Database ( 41 )—were related to support for redistribution, but did not find a significant effect ( b = 0.002, SE = 0.004, 95% CI % = [-0.006, 0.010], P = 0.643). This result suggests that when growing inequality is driven by the income gains at the very top of the distribution, it may not necessarily be reflected in people's preferences for redistribution.

Both the upward social comparison hypothesis and concurrent overrepresentation of rich individuals in the media suggest that people may be more accurate in estimating the incomes of the richest individuals compared to those in lower-income groups. Our findings stand in contrast to these predictions and show that people tend to under estimate the incomes of the richest, while providing less biased estimates for those in lower income percentiles. The fact that we observed less precise estimates and underestimation for the richest does not mean that the drivers leading to more accurate estimates or overestimation are not present, but instead that they are likely less dominant than the drivers leading to underestimation.

It is likely that several factors, including both cognitive and systemic factors, jointly influence people's judgments about the upper part of the income distribution (e.g. 42 , 43 ). For example, according to the network hypothesis, higher-income individuals have more exposure to top-income individuals and may therefore be less likely to underestimate the income of the top 1%. Indeed, in an additional analysis of data from Studies 1 and 1b, we find that participants who themselves are in the top 10% of incomes are also more accurate in their perceptions of top 1% individuals in comparison with all other participants ( P = 0.003, Z = 2.973, r = 0.122 for Study 1a and P < 0.001, Z = 3.703, r = 0.139 for Study 1b). However, even in this subset of the population, there is a remaining underestimation of the top 1%, suggesting that other mechanisms likely continue to be implicated. In fact, in Studies 2a and 2b, we were able to remove the potential influence of systemic barriers and the potential for network effects through our experimental designs and continued to find a unique underestimation of the top 1%, suggesting that cognitive biases also contribute to this effect.

Our pattern of results—the increasing underestimation at the upper echelons as we ascend in the income distribution—is consistent with selective scope insensitivity at the very top of the income distribution. The mechanisms underlying scope insensitivity suggest that instead of the quantity of a target object (e.g. the exact amount of dollars owned by a rich person), the affect triggered by the prototypical image of the object (e.g. a rich person) conveys meaning to individuals ( 27 , 31 , 32 ). As a result, an additional amount of income in upper echelons of the income distribution may trigger a weaker affective response than the same amount of additional income in lower parts of the income distribution. That is, from the perspective of an observer, a person earning $1.3 million—the average income of the richest 1% of the US population ( 44 )—is seen as less different from a person earning $1.4 million than the same absolute difference at lower income levels, for instance, between $50,000 and $150,000$. This is exactly what we observed in Study 2b, where participants’ affective response to different income levels did not proportionally vary in response to the differences in income.

However, we make clear that this evidence is not definitive evidence in favor of scope insensitivity. One potential constraint on our interpretation of these findings is that incomes are theoretically unconstrained (i.e. incomes can go higher and higher), whereas we bounded the scale for participants’ emotional response between 0 and 100. That is, it is possible that study participants opted to wait for a potentially higher income that never came, and which therefore may in part contribute to our observed pattern of results. While our evidence suggests a plausible cognitive mechanism underlying the observed pattern of results, future research could investigate whether other cognitive processes, including the underweighting of rare events in the averaging process (e.g. 35 ) or magnitude neglect (e.g. 26 ) may also contribute to the selective underestimation we observe here.

Our findings also suggest that it is unclear whether correcting perceptions about the income of the top 1% may necessarily lead to a significant change in redistributive preferences. Consider that prior intervention studies which seek to provide people with accurate information about incomes along the income distribution either do not significantly affect support for redistribution ( 6 ) or only weakly do so ( 40 ). It is possible that the presence of cognitive biases—in line with the current research—is particularly pernicious and difficult-to-intervene on, complicating progress toward increased support for redistribution ( 25 ). d

A limitation of our findings is that all reported studies collected data from US participants, raising the question whether our findings are generalizable to other populations. We provide preliminary evidence that our main findings may also replicate around the world in the same supplementary study referred to above (SS1, see detailed methods reported in the Supplementary Materials ; N 1999 = 23,288 and N 2009 = 51,970), where we used participants’ income estimates for different occupations to approximate levels of perceived inequality in 19 and 40 countries for 1999 and 2009 which we compared to objective income data from the World Inequality Database. While the results of this supplementary study are in line with our main findings, we urge caution in viewing these as conclusive data given rough occupational estimates and encourage future research to further investigate the robustness of these results.

Another limitation of our study is that we are unable to pinpoint the extent to which the geographical scale used during the elicitation in Studies 1a and 1b (i.e. the county level) impacted our results. It is possible that at different geographical scales (e.g. the state level), people may rely on different cues, such as on information from the media, when making their estimations, which could potentially lead to different results—a possibility we encourage future research to examine. Finally, we acknowledge that asking people to make numeric estimates may not necessarily map on to how they experience and respond to inequality in everyday life (see e.g. 10 , 36 ). As a result, we encourage future research to adopt a broader variety of methods, including nonnumerical and more experiential measures, to examine whether the selective underestimation of the incomes of the richest which we suggest contributes to the underestimation of inequality more broadly also manifests in the way people commonly think about and respond to inequality.

In sum, our theory and findings suggest that people are uniquely insensitive to the incomes held by individuals at the top of the income distribution. This takes on particular importance given that increases in inequality in many developed countries are often located in the disproportionate growth of incomes among the top 1% ( 1–3 ). While the recognition of inequality is commonly viewed as a critical factor in increasing support for redistributive policies (e.g. 46–49 ), the current research highlights how cognitive biases may complicate people's recognition of inequality particularly among the richest—and thereby impede progress for more redistributive policies ( 32 ). Beyond summary measures of inequality, research and policy may also need to shift toward being more sensitive to where inequality is concentrated ( 50 ).

Only current US residents and those who passed the attention check were able to participate and complete the survey. Respondents were paid US$1.30 for their participation. To increase data quality, we excluded inattentive participants, defined as those who answered 0 or 1 for every estimate, who did not write monotonically increasing income distributions, and who indicated distributions that were not realistically possible. That is, we excluded distributions that only had one increase throughout the distribution (e.g. 10, 10, 10, 10, 10, 20, 20, 20, 20, 20, 20), had no increase in the distributions (e.g. 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10), had “0” for at least four percentiles (e.g. 0, 0, 0, 0, 10, 20, 30, 40, 50, 60), had a one-point increase for all percentiles (e.g. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11), or reflected the percentiles themselves (e.g. 10, 20, 30, 40, 50, 60, 70, 80, 90, 95, 99). See Supplementary Materials for the number of distributions that we excluded for each category. The final sample size after these exclusions consisted of 593 participants (54.8% female, M age = 46.59). Note that the analysis without any exclusions yielded qualitatively congruent results. The full survey, the calculation of the objective thresholds for each county, the detailed results for the clustered Wilcoxon tests in each percentile, and the robustness tests are available in the Supplementary Materials . Study 1a was approved by the Institutional Review Board of Harvard Business School (IRB20-1176). We confirm that informed consent was obtained from all participants.

Respondents were paid a base reimbursement of US$1.30 for their participation. We applied the same exclusion criteria as in Study 1a. The sample size after exclusions consisted of 711 participants (47.12% female, M age = 36.18). The income shares were calculated identically to Study 1a. The full survey, calculation of the objective thresholds for each county, detailed results for the clustered Wilcoxon tests in each percentile, and robustness tests are available in the Supplementary Information .

The analyses testing the effect of wagering on the accuracy of the estimations were not part of the preregistration. In the preregistration, we indicated that we aimed to recruit 1,000 participants but we decided to stop data collection by 934 as the rate of new individuals willing to participate in the study became so low that it was unrealistic to reach our target number within a sensible timeframe. We did not analyze the data before making the decision to stop data collection. To make more conservative estimates, we used two-sided tests for all of the analyses. Study 1b was approved by the Institutional Review Board of Harvard Business School (IRB21-0364). We confirm that informed consent was obtained from all participants.

Studies 2a and 2b

The presentation order of the control and treatment condition was randomly assigned and counterbalanced across participants. The distribution of presented incomes was matched with data provided by the US Census Bureau with respect to the mean and the percentage of people belonging to different income brackets. To do so, we pooled some of the income brackets while we calculated the weighted mean and the total proportion of people in the new income brackets. Afterward, we randomly generated two sets of numbers with the mean of each income bracket. The number of generated incomes was proportional to the percentage of people in the given income bracket. The presentation of the two societies with different income values was counterbalanced between the two conditions, and their order was randomized. The exact income distributions are given in the Supplementary Materials . The position of the richest individual in the top 1% treatment condition varied and was counterbalanced between the 5th, 25th, 50th, 75th, and 95th positions, while the position of the 2–10% of individuals in the top 10% was randomly assigned during the presentation.

Measuring perceived inequality can be sensitive to the units of measurements (e.g. 33 , 45 ). Eriksson and Simpson ( 33 ) provided evidence that asking participants to express their estimates as averages instead of proportions leads to more accurate responses. Accordingly, after the presentation of the income distributions, we asked participants the following questions: What do you think is the average income of the richest/second/middle/fourth / poorest 20% of the individuals in the presented society? The objective income average for each quintile was calculated from the true values of the distributions.

In both Studies 2a and 2b, respondents were paid US$2.40 base reimbursement for their participation. The full surveys, the incomes presented in Studies 2a and 2b, the detailed results for the Wilcoxon tests in each quintile, and the robustness tests are all available in the Supplementary Materials . As opposed to the preregistration, we used two-sided tests for all the analyses to make more conservative conclusions. Studies 2a and 2b were approved by the Institutional Review Board of Harvard Business School (IRB21-1123). We confirm that informed consent was obtained from all participants.

For participants who did not know their county, we provided an easy lookup tool that cross-referenced their county matched by their zip code.

Note that in contrast to our findings, Chambers et al ( 16 ). found in their Study 3 that participants overestimated the cutoff for the top 1% of earners. It would be interesting to investigate the potential reasons behind these disparities (e.g. Chambers et al. studied the reported cutoff points in a two-choice paradigm while we asked participants to freely indicate any number indicating the average incomes; for a more detailed discussion, see also Jachimowicz et al. ( 12 )).

While this was not a focus of our research, we also recommend future research to further explore why people sometimes overestimate the incomes held by lower-income percentiles. For instance, it is possible that these reflect system justifying beliefs, i.e. that people hope that lower-income individuals are richer than they really are (e.g. in line with Kai and Jost ( 35 ) and Ward and King ( 36 )).

A related mechanism may be whether participants think about specific individuals who may be part of the top 1% income earners, or more abstractly think about top 1% income groups. Consider that in one of their studies, Chambers et al. ( 16 ) asked participants to estimate the number of people in very-high income buckets (i.e. $1m to $4.9m, $5m and above), and find that participants overestimated how many people in the United States are within each bucket. In contrast, Walker et al. ( 45 ) show that participants are more tolerant of inequality when focusing on specific individuals who are at the top of the income distribution, in contrast to the top 1% as a group. Given these mixed findings, we encourage future research to further disentangle how the perception of inequality may differ when focusing on specific individuals versus the top 1% in society more broadly.

Supplementary material is available at PNAS Nexus online.

The work of B.S. was supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences and the ÚNKP-22-5 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund. The work of Barnabas Szaszi was supported by the Eötvös Loránd University Excellence Fund (EKA).

The analysis plan for all studies was prepared by B.S. and H.H., with revisions provided by J.M.J. J.M.J., O.P.H., and J.T. designed and conducted Study 1a. B.S., H.H., J.M.J., O.P.H., and J.T. designed and conducted Study 1b. Studies 2a and 2b were designed by B.S. and H.H., with revisions provided by J.M.J. H.H. performed the analyses. B.S. wrote the first version of the manuscript, and J.M.J., H.H., O.P.H., and J.T. provided critical revisions.

Our preregistration specified that we would perform all analyses based on income shares. Following the suggestion of an anonymous reviewer, we opted to conduct analyses for all of our studies directly on the nontransformed data, i.e. not converting estimated thresholds into income shares. We made this change for several reasons: (i) converting to income shares could potentially yield different results depending on the measure used, (ii) it might create an artificial underestimation in the lower percentiles, and (iii) it could bias the results by extrapolating based on potentially questionable assumptions. Importantly, both the originally planned and preregistered analyses, and this different way of analyzing the data lead to qualitatively equivalent conclusions.

The HTML code of the experiments, complete surveys and materials, the anonymized data, the preprocessing, and the analysis codes for each study are publicly available on the Open Science Framework ( https://osf.io/hszyp/ ). Data for Study 2 are available for download at https://issp.org/data-download/by-year/ .

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WRIT 0020-307 202430 Critical Writing Seminar: Craft Of Prose: Researching the White Paper

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Research the White Paper

Researching the white paper:.

The process of researching and composing a white paper shares some similarities with the kind of research and writing one does for a high school or college research paper. What’s important for writers of white papers to grasp, however, is how much this genre differs from a research paper. First, the author of a white paper already recognizes that there is a problem to be solved, a decision to be made, and the job of the author is to provide readers with substantive information to help them make some kind of decision--which may include a decision to do more research because major gaps remain.

Thus, a white paper author would not “brainstorm” a topic. Instead, the white paper author would get busy figuring out how the problem is defined by those who are experiencing it as a problem. Typically that research begins in popular culture--social media, surveys, interviews, newspapers. Once the author has a handle on how the problem is being defined and experienced, its history and its impact, what people in the trenches believe might be the best or worst ways of addressing it, the author then will turn to academic scholarship as well as “grey” literature (more about that later). Unlike a school research paper, the author does not set out to argue for or against a particular position, and then devote the majority of effort to finding sources to support the selected position. Instead, the author sets out in good faith to do as much fact-finding as possible, and thus research is likely to present multiple, conflicting, and overlapping perspectives. When people research out of a genuine desire to understand and solve a problem, they listen to every source that may offer helpful information. They will thus have to do much more analysis, synthesis, and sorting of that information, which will often not fall neatly into a “pro” or “con” camp: Solution A may, for example, solve one part of the problem but exacerbate another part of the problem. Solution C may sound like what everyone wants, but what if it’s built on a set of data that have been criticized by another reliable source? And so it goes.

For example, if you are trying to write a white paper on the opioid crisis, you may focus on the value of providing free, sterilized needles--which do indeed reduce disease, and also provide an opportunity for the health care provider distributing them to offer addiction treatment to the user. However, the free needles are sometimes discarded on the ground, posing a danger to others; or they may be shared; or they may encourage more drug usage. All of those things can be true at once; a reader will want to know about all of these considerations in order to make an informed decision. That is the challenging job of the white paper author.   The research you do for your white paper will require that you identify a specific problem, seek popular culture sources to help define the problem, its history, its significance and impact for people affected by it. You will then delve into academic and grey literature to learn about the way scholars and others with professional expertise answer these same questions. In this way, you will create creating a layered, complex portrait that provides readers with a substantive exploration useful for deliberating and decision-making. You will also likely need to find or create images, including tables, figures, illustrations or photographs, and you will document all of your sources.

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Should my child be given antibiotics? A systematic review of parental decision making in rural and remote locations

Stephanie A. Marsh 1 ,
Sara Parsafar 2 &
Mitchell K. Byrne 1

Antimicrobial Resistance & Infection Control volume 13 , Article number: 105 ( 2024 ) Cite this article

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Metrics details

The emergence and growth in antibiotic resistant bacteria is a critical public health problem exacerbated by the misuse of antibiotics. Children frequently succumb to illness and are often treated with antibiotic medicines which may be used improperly by the parent. There is limited evidence of the factors influencing parental decision-making about the use of antibiotics in low-resource contexts. The aim of this systematic review was to understand and describe how parents living in rural and remote locations make choices about their children’s antibiotic use.

The CINAHL, Web of Science, Medline, Scopus and Academic Search Premier databases were systematically searched from 31 January until 28 June in 2023. No date restrictions were applied and additional search methods were utilised to identify further studies that met inclusion criteria. Eligibility criteria included studies which reported on factors contributing to parental decisions about their children’s use of antibiotics in rural and remote settings. The Joanna Briggs Institute Critical Appraisal Checklists were employed to evaluate studies. Characteristics and findings were extracted from studies, and data was synthesised descriptively and presented in summary tables.

A total of 3827 articles were screened and 25 worldwide studies comprising of quantitative, qualitative and prospective designs were included in the review. Studies that reported the number of rural caregivers consisted of 12 143 participants. Data analysis produced six broad themes representing the mechanisms that influenced parents in their access and use of antibiotics: the child’s symptoms; external advice and influences; parent-related determinants; barriers to healthcare; access to antibiotics; and socio-demographic characteristics.

Conclusions

A number of factors that influence parents’ prudent use of antibiotics in rural contexts were identified. In seeking to enhance appropriate use of antibiotics by parents in rural and remote settings, these determinants can serve to inform interventions. However, the identified studies all relied upon parental self-reports and not all studies reviewed reported survey validation. Further research incorporating validated measures and intervention strategies is required.

Registration details

Should my child be given antibiotics? A systematic review of parental decision making in rural and remote locations ; CRD42023382169; 29 January 2023 (date of registration). Available from PROSPERO.

Antibiotics are critical in the treatment of infections caused by bacteria and can be lifesaving medicines in early life [ 1 ]. However, widespread and indiscriminate use of antibiotics is a significant contributor to the development of drug resistant pathogens, known as antimicrobial resistance (AMR) [ 2 , 3 ]. AMR is increasing on a global scale, and currently accounts for approximately 700 000 deaths each year worldwide. This rate is predicted to increase exponentially to 10 million deaths by 2050, deepening the impact on health systems as infections become harder to treat [ 4 ]. Accordingly, the World Health Organization (WHO) has ranked AMR in the top ten global health threats [ 5 ]. Children are vulnerable to frequent bouts of illness [ 6 ] and are among the highest consumers of antibiotics [ 1 , 7 ]. The United Nations Children’s Fund (UNICEF) has described AMR as “…perhaps the greatest threat to child survival and health of this generation” [ 8 p.2]. However, parental use of antibiotics with their children can be a key contributor to AMR. For example, despite the common experience of respiratory illness in childhood and the frequent use of antibiotics, only a small proportion of upper respiratory infections are of bacterial origin requiring antibiotic treatment [ 2 ].

The drivers of antibiotic overuse and misuse in children are multi-factorial and relate to both over-prescribing by health professionals [ 9 ] and the way that parents use antibiotics, such as autonomous practices [ 10 ] and failure to follow antibiotic treatment instructions [ 4 ]. Given that parents are the end-users and decide on behalf of the child how medication is obtained and used [ 11 ], understanding parent choices in their use of antibiotics is crucial to the determinants of inappropriate antibiotic use [ 12 ]. Parental decisions about antibiotic use with their children are influenced by a range of person and context variables. Previous systematic reviews have examined and quantified non-prescription antibiotic use in children [ 3 , 13 ], describing parental knowledge about the use of antibiotics [ 2 ] and attitudes of parents about antibiotic prescribing in children as key drivers in antibiotic use [ 4 ]. Furthermore, systematic review findings indicate that residing in a rural location, and distance to healthcare, are associated with parents using antibiotics without consulting a doctor [ 13 ], a practice linked to the emergence of drug resistance [ 14 ]. This systematic review builds upon prior research and reviews by examining patterns in the decisional processes of parents living exclusively in rural communities around the world towards their use of antibiotics. This research also draws upon theoretical models explaining health-related behaviours to interpret and understand the review findings.

The mechanisms by which rurality and healthcare access influence parental decisions about antibiotic use are integral to understanding how parents in such locations can be supported to make more judicious decisions regarding the use of antibiotics with their children. Recent Australian research examining parents living in rural locations found that parental decisions about their children’s antibiotic use were influenced by fear of serious illness, and exacerbated by limited access to healthcare [ 15 ]. The influence of contextual factors is pertinent, as high rates of antibiotic resistant bacteria have been detected in children living in rural communities [ 16 ]. Drug resistant bacteria in children is especially concerning because of the contraindications of some antibiotics there are fewer options available to safely treat children [ 17 ].

Recent Australian research involving parents living in remote areas [ 15 ] provides some insight into how the context of rurality and healthcare access influence parental decisions. However, there are no systematic reviews which have examined the decision-making processes and influences of parents towards their children’s antibiotic use in rural, resource-limited settings. Understanding the drivers of parental behaviour in rural contexts can help to guide policy and target interventions to slow the growth of AMR. Thus, the objective of this review was to systematically describe the decision-making process of rural parents regarding their use of antibiotics. We sought to address the following research question: What factors influence the decisions of parents with children living in rural and remote locations in their use of antibiotics? Using the insights drawn from the recent Australian study [ 15 ] to facilitate search terms, we reviewed the international literature to identify factors influencing parents to initiate antibiotic therapy and the motivators of their antibiotic use behaviours.

A pre-defined research protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) prior to the commencement of the review. This research was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines to ensure transparency and accurate reporting [ 18 ]. No amendments were made to the protocol during the review process. (Further details of the completed PRISMA 2020 checklist and adherence to the statement can be found in Additional file 1 ).

Eligibility criteria

Inclusion and exclusion criteria were pre-specified in the study protocol and applied during screening. Worldwide studies available in English were included, and no restrictions were placed on the publication period. Both peer-reviewed and grey literature were accepted. Studies were eligible if they provided data on the decision-making process of parents living in rural and remote locations in their use of antibiotics with their children (aged 0–18 years). This included an examination of all factors influencing parent decisions to use antibiotics, and factors contributing to how antibiotics were acquired and used. Parents were defined in accordance with the National Library of Medicine as: ‘persons functioning as natural, adoptive, or substitute parents’, such as caregivers [ 19 ]. Factors were described as circumstances, facts or influences contributing to parental decisions. We considered quantitative and qualitative designs, mixed methods, observational, prospective, systematic reviews, cross-sectional and longitudinal studies. Studies incorporating both rural and urban parents met inclusion criteria if there was clear delineation between urban and rural parent responses. If multiple medications were examined, or other population sub-groups were in the sample, these studies were included if the exclusive results were provided for antibiotics and parents. We excluded studies without data (i.e., editorials, protocol designs and letters) and intervention studies relating to antibiotic stewardship and treatment compliance. Studies that did not provide data on the decision-making process of parents towards their children’s antibiotic use, non-parent/caregiver samples and studies specifically examining other antimicrobial agents (antiviral, anti-fungal, anti-parasitic), or other medicines, were excluded. Studies based in urban and semi-urban settings were also excluded from the review.

Search strategy

Five electronic databases were systematically searched: Web of Science; Scopus; EBSCOhost databases (Academic Search Premier, CINAHL and Medline). The search was performed from 31 January 2023 and monitored weekly through database alerts until 28 June 2023. A final update of each database was performed on 16 June 2023. Our search strategy included a combination of key words and Medical Subject Heading (MeSH) terms. Search terms were developed using a variation of the Population, Intervention, Comparison, Outcomes, Study design/Setting (PICOS) elements and were guided by prior study findings [ 15 ]. The search strategy was reviewed and refined by an academic librarian. Terms were separated into their synonym groups when combined in searches to build a multi-line search strategy, connected with Boolean connectors (AND/OR). A preliminary search was conducted using the search string to test for the identification of records. Search terms were adapted for use to account for changes in database symbols, or other search syntax, particular to a database. Database-specific filters were applied where available. (Details of the full search strategies for all databases are outlined in Additional file 2 ). To identify additional articles, the reference lists of studies eligible for full-text review and grey literature websites/search engines, were searched between 3 and 22 March 2023. Grey literature covered both accessible and inaccessible articles and included searching: Trove; Open Grey; OpenDOAR; NZresearch.org.nz; MedNar; Western Pacific Region Index Medicus; Clinical Trials Search Portal; Theses Canada; PsycINFO; and Google Scholar. A mix of key words and simplified search strings were used to account for differences in search interfaces after consultation with a research librarian. (Further details of the supplementary searches are provided in Additional file 2 ).

Selection of studies

Records identified from electronic databases and other sources described were downloaded and stored in EndNote software version X9. All records were screened for duplication by the principal reviewer (SM) using EndNote tools and through a manual process of checking, identifying and removing duplicate records. The titles and abstracts of records were screened by SM using a pre-defined decision tree to guide judgements in the screening and selection of studies for inclusion in the review. The decision tree was a methodological approach used to assist the reviewers to stay organised and transparent in their approach and to ensure that the inclusion and exclusion of studies was based on predefined criteria to minimise the risk of bias in the review process. Fidelity checks were conducted by the other reviewers (MB and SP) on a random selection (10%) of included and excluded records. Discrepancies were resolved through team discussion, or referred to the third reviewer to determine study inclusion. Articles included in the next stage, underwent full-text evaluation by SM using a full-text decision tree tool to assess study eligibility. (Further details of both decision trees are available in Additional file 3 ). A random sample (10%) of full-text articles were reviewed by (MB and SP) to check decisions against the decision tree criteria. Inconsistencies in opinion were discussed until a consensus was reached, or when there was disagreement, the third reviewer made the final decision regarding study inclusion. During screening, one study investigator was emailed to confirm participant characteristics, to no avail. Subsequently, study inclusion was discussed amongst the researchers until agreement was attained.

Data extraction

A standardised format was used to collect and enter study data into a Microsoft Excel spreadsheet using labelled columns. The initial extraction was performed by one reviewer (SM) and re-checked for accuracy. Subsequently, two other members of the research team (MB and SP) crossed-checked the extracted data. Findings were discussed and agreement was reached on the corresponding information. In one study, participants were described as ‘parents/carers of young children’ and the age range of the children was not specified [ 20 ]. However, we included this study based on the assumption that ‘young children’ was the same as pre-adolescents (primary school age and younger), given that parents were recruited through early childhood education services and playgroups. The following pre-specified data was collected from each eligible study, similar to the information extracted in prior reviews [ 4 ]: author name; year of publication; country; study aim; study setting/context; participant information (caregiver and child characteristics); study design and methodology; key findings (principal outcomes and results relevant to the current research); and study limitations. The primary outcome of interest was: the drivers/determinants of parents’ decisions towards the use of antibiotics with their children. Variables investigated included factors predisposing parents to use antibiotics (factors associated with use), and determinants of how antibiotics were accessed and used by parents (i.e., prescription/non-prescription use, asking prescribers for antibiotics, and antibiotic adherence behaviour). We considered any measure of parental decision-making, which was predominantly self-report.

Critical appraisal

We assessed the possibility of bias and the methodological quality of studies included in the next phase of the review, using the Joanna Briggs Institute (JBI) critical appraisal checklists. JBI has shifted towards using the term ‘risk of bias’, notably for quantitative analytical designs, which does not include assessing quality constructs. However, different terminology remains, and is suitable when assessing qualitative or other types of research evidence [ 21 ]. The JBI tools were selected according to the design of each study assessed, and all items in the corresponding checklists were utilised. Subsequently, we employed the following four JBI checklists: studies reporting prevalence data; qualitative research; cohort studies; and analytical cross-sectional studies. Mixed-methods designs were appraised using the checklist reporting prevalence data, as well as the checklist for qualitative research. Two reviewers (SM and SP) independently assessed full-text studies (i.e., appraisals were performed by the principal reviewer and checked by SP). A proportion (10%) of randomly selected studies were assessed by the third reviewer (MB) using the JBI tools. Responses were recorded using the JBI forms and comments were added to support judgements, where necessary. Discrepancies in appraisals were managed through discussion between the reviewers to reach agreement.

A pre-determined JBI score of 60% or above was decided by the review team, which is indicative of moderate to high-quality studies [ 22 ] and has been applied in past reviews [ 3 ]. Inclusion of studies scoring low on JBI may jeopardise the validity of the review findings [ 23 ]. Thus, only studies reaching 60% or higher ‘yes’ results after discrepancies between reviewers had been resolved were included in the review. For mixed-methods designs, if the study met only partial inclusion, a reasoned and collaborative approach was employed by the research team [ 24 ] to consider the component that passed critical appraisal. We used the following score ranges to rate the potential risk of bias of individual studies: low risk of bias for studies achieving 70% or more ‘yes’ scores; moderate risk of bias for studies obtaining between 50 and 69% ‘yes’ scores (noting studies below 60% were excluded); and high risk of bias if the number of ‘yes’ scores was below 50% [ 25 ].

Data synthesis

Data from individual studies included in the review was summarised by tabulating extracted information in a Microsoft excel spreadsheet for transparent reporting and to present a comparison of the findings. Studies were ordered within the spreadsheet by the year of publication to present the most recent research in the field to the earliest. A narrative synthesis of the findings was provided following the guidance of Popay and colleagues (2006) [ 26 ]. There was considerable heterogeneity in the study methods and approaches used, subsequently, a meta-analysis was not performed. However, the purpose of the review was to describe, rather than quantify, a process of decision-making. Key findings data was analysed to identify common patterns and differences across studies. This information was then synthesised and summarised descriptively in ‘Primary findings’ tables to address the research question. Comparisons were made between Australian and international research, where applicable. Primary findings were categorised into groups for the synthesis: (1) the process of decision-making to use or not use antibiotics i.e., influences on antibiotic use (2) factors contributing to specific behaviours with antibiotics identified i.e., non-prescription use of antibiotics, non-adherence to antibiotic treatment, requests for antibiotic prescriptions. Broader themes of the mechanisms underlying antibiotic use decisions were identified and categorised in the tables of primary findings. Data synthesis wasn’t categorised according to the age of the child as nearly all studies sampled children < 12yrs. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was not used to assess the certainty of evidence based on the limitation that all studies which are non-randomised control trials are rated as low evidence by GRADE [ 27 ].

Study selection

Electronic database searches and registers identified 4324 records and an additional 22 records were found via citation and grey literature search. No unpublished articles were identified. However, some grey literature sources searched both accessible and inaccessible articles. This assisted to uncover records that were not identified through the original electronic database search. After duplicate records were removed, 3805 titles and abstracts were screened. Most records excluded at this stage were unrelated to antibiotic use. Following this process and the identification of records from reference lists and other methods, 88 eligible full-text articles were sought. Only 1 report was unable to be retrieved in a full-text English language version. A total of 87 full-text articles were reviewed for eligibility. Reports were excluded for the following three reasons using the full-text decision tree tool: (1) participant characteristics were not suitable (2) the study did not provide exclusive results for parents/caregivers, or antibiotics, or parents living in rural or remote areas (3) the study did not provide data on the decision-making process of rural parents towards their children’s antibiotic use. Three studies appeared to meet inclusion criteria but were excluded because of difficulty delineating specific antibiotic use decisions for rural parents [ 28 , 29 ], or we were unable to determine if both urban and rural sub-districts were amongst the findings [ 30 ]. During the final phase of screening, 32 studies were evaluated using the JBI checklists. Two mixed-methods studies that met partial inclusion were excluded from the review after team discussion. These were excluded because either the quantitative study was developed based on the qualitative research, which did not reach JBI score requirements, or the qualitative component met inclusion, but did not provide data relevant to the research question. After all appraisals were completed, 25 studies remained, and were included in the review. Figure 1 details the study selection process using the PRISMA 2020 flow diagram.

PRISMA 2020 flow diagram outlining the study selection process

*Reasons for full-text exclusion: Reason 1 : participant characteristics were not suitable; Reason 2 : the study did not provide exclusive results for parents/caregivers, or antibiotics, or parents living in rural or remote areas; Reason 3 : the study did not provide data on the decision-making process of rural parents towards their children’s antibiotic use

Characteristics of studies

The 25 studies included in the review represented 14 countries across 6 continents: Asia (14); Africa (7); Central America (1); South America (1); Europe (1) and Australia (1). The highest number of studies (6) were conducted in Vietnam [ 31 , 32 , 33 , 34 , 35 , 36 ]. Publication periods spanned between 1996 and 2022. The design of 18 studies was quantitative [ 33 , 34 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 ], 6 were qualitative [ 20 , 31 , 35 , 52 , 53 , 54 ] and 1 study was prospective [ 32 ]. Sample sizes varied from 13 to 3117 caregivers [ 48 , 52 ] and up 4087 children [ 33 ] and depended on the study design. Cross-sectional studies had the largest samples [ 33 , 37 , 48 ] whereas qualitative designs with only a proportion of rural caregivers had the smallest [ 52 ]. Studies recruited either caregivers (parents, grandparents, other relatives, or carers), or specified parents or mothers. However, across all studies, most respondents were mothers. Only 2 studies included a small proportion of children > 12yrs [ 41 , 51 ] and the majority sampled were children < 6yrs. One study stated that 2% of children were > 10yrs [ 45 ], and another specified ‘young children’ [ 20 ]. All other studies sampled children < 7yrs. Of the included studies: 18 studies examined the knowledge, attitudes or perceptions and behaviours of parents towards the use of antibiotics for their children [ 31 , 32 , 34 , 37 , 38 , 39 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 49 , 51 , 52 , 53 , 54 ]; 4 studies investigated parent opinions and practices towards childhood illnesses and health-seeking behaviours [ 20 , 40 , 48 , 50 ]; and 3 studies examined patterns of drug use, including antibiotic use, amongst parents [ 33 , 35 , 36 ]. (Additional file 4 describes the characteristics and key findings of individual studies included in the review and includes all data used for analysis).

Risk of bias quality assessment

The risk of bias for studies included in the review was classified as low for 16 studies [ 20 , 31 , 32 , 33 , 34 , 35 , 36 , 38 , 41 , 42 , 44 , 46 , 51 , 52 , 53 , 54 ] and moderate for 9 studies [ 37 , 39 , 40 , 43 , 45 , 47 , 48 , 49 , 50 ]. (A summary of the risk of bias assessments, including each domain/item assessed for all studies appraised is provided in Additional file 5 ). There is a possibility of recall and response bias in all of the studies, as each depended on parent self-reports of their experiences, perceptions and practices [ 4 ]. For most quantitative studies, it was unclear if the survey instrument had undergone full measurement validation. In some studies, pre-testing and pilot studies had been conducted (44%), indicating relative validation of the measurement tool [ 38 , 40 , 42 , 43 , 44 , 45 , 46 , 48 ]. Other studies didn’t discuss instrument validation (33%) [ 33 , 36 , 37 , 39 , 41 , 50 ]. Only a minority of studies (22%) reported the survey had been validated [ 34 , 47 , 49 , 51 ]. All qualitative and prospective studies were considered low risk of bias [ 20 , 31 , 32 , 35 , 52 , 53 , 54 ]. However, some reporting elements were missing from the qualitative research: most did not include information about the researcher’s cultural or theoretical orientation (67%); and the majority of qualitative studies did not report the researcher’s philosophical perspective (67%).

Tables 1 , 2 , 3 and 4 synthesise the primary findings of the review and represent the finding of themes generated from data analysis. The themes and sub-themes describe the factors found to underlie parent decisions about antibiotic use. We established six themes that impacted the decisions of parents residing in rural locations in their use of antibiotics: the child’s symptoms; external advice and influences; parent-related determinants; barriers to healthcare; access to antibiotics; and socio-demographic characteristics. Mechanisms covered by these themes contributed to overuse and misuse behaviours related to the access and use of antibiotics in rural contexts and were tabulated according to the four core areas of investigation (i.e., influences on antibiotic use, non-prescription use of antibiotics, non-adherence to antibiotic treatment, requests for antibiotic prescriptions). The tables present data on when, why and how parents engaged with antibiotics in rural setting. (Further details of data coding and thematic development can be found in Additional file 6 ).

Table 1 describes the factors that motivated parents to use or not use antibiotics with their children.

Table 2 details the predictors of parental use of antibiotics without medical guidance.

Table 3 outlines the factors that influenced parents to cease their child’s antibiotic therapy early and not complete a full treatment course.

Lastly, Table 4 indicates the reasons parents placed demand on doctors to prescribe antibiotics for their child.

The findings of this review suggest that six themes underpinned the decisions of parents living in rural and remote settings towards their use of antibiotic medicines. The first theme was the ‘child’s symptoms’ , which represented findings concerning the nature and severity of illness. Our results highlight that parents perceived antibiotics as appropriate in the treatment of a variety of symptoms exhibited by their children including cough, fever, diarrhea, respiratory illness, breathing impairment, and ear infections. The nature of the child’s symptoms both motivated parental expectations for the provision of antibiotics and influenced antibiotic use, including autonomous practices (without reference to medical advice), which has been substantiated in prior reviews [ 13 ]. In more than half of the studies, parents used antibiotics autonomously to treat their children’s cough, diarrhea, fever, colds/respiratory infection and breathing difficulties. Cough and fever were the symptoms associated most with parental expectations to use antibiotics, and antibiotic use in general, including both prescribed and unprescribed use. However, when only non-prescription antibiotic use was examined, children with fever received unprescribed antibiotics in fewer studies than those with cough and diarrhea symptoms. This finding might be explained by research in China which reported that while parents were most concerned about fever and cough symptoms, they were less likely to use antibiotics to treat fever without consulting a doctor [ 41 ]. The severity of the child’s illness, duration and number of symptoms influenced antibiotic use and expectations for the child to receive antibiotics [ 31 , 32 , 33 , 37 , 39 , 48 ], which is supported by previous research findings [ 4 , 15 ]. It is likely that parental use of prescribed antibiotics was influenced by the prescriber’s decisions and advice [ 31 , 32 , 39 ], highlighting the importance of the opinions of others in decision-making. However, in relation to unprescribed use, parents treated their children with antibiotics for perceived minor illness in four studies [ 32 , 35 , 43 , 51 ] and in two studies when the illness was more severe or multiple symptoms were reported [ 33 , 37 ]. This finding may reflect that parents might try to seek medical advice for their child when the illness is believed to be serious, but appear to use antibiotics autonomously for a range of symptoms and severity levels when medical advice is less available.

The second theme that emerged from our analysis was ‘external advice and influences’. This theme relates to findings that parents were influenced by the opinions and advice of others when making decisions about the use of antibiotics with their children. As expected, prescriber advice informed parental understanding of when antibiotics were required in a number of studies [ 31 , 32 , 39 , 40 , 41 , 42 , 43 , 49 , 51 ]. In two studies, even when parents perceived antibiotics were not necessary, they adhered to medical recommendations to treat their child with antibiotics [ 31 , 32 ], highlighting the value placed on guidance from prescribers. Information from doctors about antibiotics has been identified as an important source of knowledge for parents in past research [ 13 ]. However, parents also considered the advice of friends and family, such as those with more experience, or ‘decision makers’ regarding their child’s treatment needs and the use of antibiotics [ 40 , 43 , 49 , 52 , 54 ]. We found that seeking advice from others contributed to parental decisions to use non-prescription antibiotics with their children. In nine studies where unprescribed antibiotics were used, parents obtained treatment advice from drug suppliers, health professionals living in their community, friends and relatives [ 32 , 34 , 35 , 44 , 47 , 48 , 49 , 52 , 54 ]. Additionally, social and cultural norms influenced autonomous antibiotic use and non-adherence behaviours. For example, parents acted in accordance with the views of others [ 53 , 54 ], were influenced by pharmaceutical promotions [ 36 ] and obtained antibiotics from people in their network [ 46 ]. Findings in respect to non-adherence behaviours highlight that external factors, such as palatability and lack of refrigeration influenced early discontinuation of the child’s antibiotic course in an Australian study [ 20 ]. This highlights that some reasons for non-adherence were child-related or influenced by socio-economic factors.

The third theme identified from this review was ‘parent-related determinants’ . This theme reflects findings that knowledge, attitudes/beliefs and cognitive factors contributed to parental behaviours with antibiotics across the four core areas of investigation. A lack of parental knowledge and confusion regarding antibiotic use [ 20 , 34 , 35 , 40 , 42 , 53 ], and beliefs about symptom improvement [ 35 , 41 , 42 , 51 , 53 , 54 ] mostly accounted for non-adherence decisions. One study identified that parents pressured prescribers for prescriptions because they perceived it was appropriate to ask for antibiotics [ 51 ]. This finding underscores the influence of attitudinal (a right to receive a prescription) or knowledge (lack of understanding of the need for antibiotics) factors on behaviour. In relation to unprescribed antibiotic use, limited knowledge about the indications for use or the risks of use was identified in numerous studies where parents used antibiotics autonomously [ 34 , 35 , 37 , 38 , 40 , 41 , 42 , 45 , 51 ]. There was some inconsistency with this finding, with other studies reporting no association between parental knowledge and unprescribed antibiotic use [ 47 ] or observing that having adequate knowledge of prescription requirements was associated with increased likelihood of retaining leftovers [ 42 ]. Nonetheless, research did indicate that knowledge played an important role in the appropriate use of antibiotics, which has been supported by past reviews [ 2 , 13 ]. However, possessing knowledge does not necessarily ensure responsible behaviours with antibiotics [ 2 ], as other factors appear to also drive autonomous practices [ 47 ]. For example, strong beliefs regarding the efficacy of antibiotics were discussed in a number of studies where non-prescription antibiotic use was prevalent [ 33 , 34 , 35 , 36 , 49 , 51 , 52 ]. Of these, four studies discussed that antibiotics were perceived as a cure-all [ 33 , 35 , 36 , 52 ], highlighting firm beliefs about antibiotics as curative drugs used to treat a range of illnesses, which likely influenced antibiotic use decisions. These results might explain why parents used antibiotics to treat many symptoms of childhood illness irrespective of the microbial source. Parental attitudes that the child’s condition is too minor to see a doctor and prior experience using prescription antibiotics to treat a similar illness, may explain parents self-treating symptoms perceived to be minor.

The results of this review identified ‘barriers to healthcare’ as a further theme. This theme includes findings of the difficulties experienced by parents in accessing health facilities in rural settings. Poor access to formal healthcare was a barrier to appropriate antibiotic use and predominantly impacted parents administering antibiotics to their children without consulting a doctor, consistent with previous research [ 13 ]. In the current review, ten studies reported on the specific mechanisms of limited access to healthcare believed to contribute to the non-prescription use of antibiotics. Insufficient time, money or service availability [ 35 , 43 , 47 , 49 , 52 , 54 ], greater distance to travel [ 36 , 37 , 46 , 53 , 54 ], lack of transportation [ 36 , 37 , 53 ] and poor road conditions [ 36 , 37 ] were challenges which influenced autonomous practices with antibiotics. Living greater than 5 miles [ 37 ] or 5 km [ 46 ] from the nearest hospital or health facility was associated with parents using unprescribed antibiotics with their children in two studies. Living far from healthcare facilities also provided the impetus to store leftover antibiotics as a strategy to manage resource limitations [ 53 ]. In seven studies citing poor access to healthcare, parents reported to obtain treatment advice from drug suppliers, family, friends from a health background [ 35 , 47 , 49 , 52 , 54 ] or parents shared antibiotics between their personal network [ 46 , 53 ]. Analysing the information in the current review does not determine whether lack of access to healthcare caused parents to seek advice from others. However, separate to a predilection to listen to non-medical advice, when there are impediments to accessing healthcare, parents may utilise other available resources to assist with decision-making, or adopt strategies to gain access to antibiotics.

The fifth theme established from data analysis was ‘access to antibiotics’. This theme relates to findings that availability of unprescribed antibiotics (i.e., over-the-counter sales, storing or sharing antibiotics) enabled autonomous use by parents. The availability of over-the-counter antibiotics at drug stores was discussed in almost half the studies as a contributor to non-prescription use [ 33 , 34 , 35 , 36 , 37 , 47 , 48 , 49 , 50 , 51 , 52 , 54 ]. In five studies, purchasing antibiotics without a prescription and storing antibiotics and leftovers in the home were associated with parents using antibiotics autonomously [ 36 , 41 , 42 , 47 , 51 ]. Antibiotic sharing also contributed to parents using antibiotics without consulting a doctor [ 46 , 52 , 53 ]. In a number of studies, drug stores were described as easily accessible in terms of distance, affordability or extended operating hours and may be negotiable in price, quantity or brand [ 35 , 36 , 37 , 48 , 49 , 50 ]. It is important to note that in some settings it was reported that unregulated drug stores were the only feasible avenue for the community to access medicines and healthcare [ 54 ]. In nine studies reporting barriers to the formal health system, parents accessed antibiotics via non-prescription sale or by sharing or storing antibiotics [ 35 , 36 , 37 , 46 , 47 , 49 , 52 , 53 , 54 ]. The findings indicate that access to unprescribed antibiotics is a strong predictor of antibiotic use. Healthcare challenges appear to exacerbate autonomous behaviours resulting in parents deciding to seek more available treatment pathways.

The final theme of this review was ‘socio-demographic characteristics’ , which includes variables associated with antibiotic use and misuse, such as the child and parents’ age, parent education, and household composition. There were no clear patterns that emerged from socio-demographic factors, which is consistent with previous research [ 13 ]. In two studies it was observed that children over 2-3yrs of age had a higher likelihood of using antibiotics [ 32 , 42 ], and increasing age of the child was associated with non-prescription antibiotic use in one study [ 51 ]. Studies in Australia and Vietnam indicate that parents may try to safeguard their young children from antibiotics [ 15 , 32 ]. However, in contrast, other research found that younger children had the highest rates of antibiotic use [ 39 , 48 ] and were more likely to be treated with unprescribed antibiotics [ 37 ]. In a Nigerian study it was opined that younger children may have received more antibiotics because of parental perceptions that illness is more serious in early life [ 48 ]. In the case of prescribed antibiotic use, we are unable to determine from our analysis of some studies if the age of the child impacted the parents’ decision to seek antibiotics, or if healthcare providers were inclined to prescribe more antibiotics based on the child’s age [ 32 , 39 ].

With respect to non-prescription use of antibiotics, the parent’s age and level of education also produced conflicting findings. For example, in Nigeria, mothers with higher levels of education were more aware of the risks of misuse and were less inclined to self-treat with antibiotics [ 38 ]. On the contrary, studies in Vietnam observed more highly educated mothers were prone to autonomous antibiotic use [ 32 , 36 ] and reported confidence in when to initiate antibiotics [ 36 ]. The mixed results produced for parent/child features and antibiotic use may reflect the number of different countries, cultures and their values. Cultural awareness and sensitivity should be considered when planning interventions to meet the needs of the target population. Nonetheless, having multiple children/household members was found to be associated with parents using unprescribed antibiotics in two Chinese studies [ 41 , 51 ]. This finding has been supported in past reviews [ 13 ] and suggests that increased experience with using antibiotics may enhance confidence to self-treat.

Theoretical models

The various themes that emerged from the analysis can be interpreted with reference to theories explaining health-related behaviours. Based on the results of this review, the most comprehensive explanation of parental behaviours with antibiotics is provided by the Theory of Planned Behaviour (TPB) and Self-Determination Theory (SDT). The TPB posits that three key constructs influence intention to perform a behaviour: attitude about the behaviour; subjective norms that others approve of the behaviour; and perceptions of control that the behaviour can be facilitated [ 55 ]. One or a combination of these variables facilitates an understanding of parental choices towards their children’s antibiotic use in rural settings. For example, the data suggests strong beliefs about the effectiveness of antibiotics in the treatment of numerous symptoms and favourable attitudes towards autonomous antibiotic use are likely predictors of antibiotic use behaviours. Associated with attitudes, deficits in antimicrobial knowledge likely contributed to the formation of parental attitudes about antibiotic use, although knowledge did not always motivate autonomous behaviour. Attitudes and beliefs were also found to contribute to non-adherence decisions and requests for antibiotic prescriptions. Our findings also indicate that advice and assent from others, subjective norms, including both medical and non-medical connections, contributed to antibiotic use and autonomous use. Relatedly, social pressure and cultural factors were also found to play a role in the non-adherence decisions of Malawian parents [ 53 ]. Perceived behavioural control to act appropriately and obtain medical guidance from a prescriber was impeded by cost, time, distance to services and limited healthcare options. While ease of availability to unregulated antibiotics facilitated antibiotic use and increased behavioural control over autonomous use decisions as a strategy to manage healthcare barriers.

Alternatively, the SDT model provides an alternative framework to understand why parents might initiate antibiotic therapy without consulting a doctor. SDT proposes that people have three core psychological needs: autonomy (i.e., the need for choice in their behaviour); competence (i.e., the need to feel capable and effective in influencing favourable outcomes); and relatedness (i.e., the feeling of connectedness, being understood and belonging with others). When the health context supports people in meeting these needs, people are increasingly motivated to be autonomous in their actions and maintain their health behaviours [ 56 ]. The data from this study suggests that unregulated access to antibiotics and support received from others in the social environment in the decision-making process towards autonomous antibiotic use, facilitates and maintains behavioural autonomy with antibiotics. Parental beliefs about the efficacy and potency of antibiotics in treating multiple symptoms likely influences feelings of competency in aiding their child’s recovery from illness by using antibiotics. Feelings of competency may be maintained by knowledge deficiencies about the risks and indications for antibiotic use. Furthermore, widespread use of over-the-counter antibiotics and acceptance of storing and sharing practices among households, likely supports feelings of relatedness and normalises behaviours utilised to access antibiotics and manage healthcare difficulties.

Summary and limitations

This review uncovered six themes representing factors which contributed to when, why and how parents in rural and remote locations accessed and used antibiotics. These insights may assist in the development of programs to facilitate the appropriate use of antibiotics in rural and remote settings. By identifying the bespoke drivers of antibiotic use by parents within context of place and culture, interventions focussing on knowledge, attitudes, social norms, and behavioural competency in the management of children’s health needs can be developed. Such bespoke interventions necessitate measurement of the drivers of target parent behaviours using reliable and valid strategies.

A number of limitations are acknowledged in this research. This systematic review was limited to studies in English. However, grey literature and reference lists were searched without date restrictions, and a range of study designs were included in order to identify as much research as possible, which was a strength of this study. Care was taken to systematically categorise studies into themes and sub-themes. Nevertheless, we acknowledge this might introduce some degree of subjectivity to data analysis. Although the review was worldwide, limited Australian studies were identified that met the inclusion criteria. This presents a need for further research in rural and remote settings of Australia to investigate the appropriate use of antibiotics on larger samples of parents. Future reviews may also consider a comparison of urban and rural parent samples to ascertain any key differences/similarities of note in how decisions are formed. Lastly, survey validation procedures of studies included in this review were underreported. This highlights an opportunity for future research to report these processes more transparently to enhance the robustness of the findings.

This study identified a number of determinants motivating parents in rural and remote areas to use antibiotics and factors which influenced their practices. Nearly all studies identified parents treating their children with non-prescription antibiotics, which was the most common misuse practice noted. Overuse and misuse of antibiotics is a critical driver in selecting and facilitating the development of drug resistant bacteria in communities. Accordingly, the results of this review give emphasis to several mechanisms that enabled antibiotic use as well as obstacles that prevented parents from making more optimal decisions about the use of antibiotics. The way in which these mechanisms inter-relate to influence the decisions and behaviour of parents should be considered when developing bespoke interventions to contain the impact of AMR in rural, low-resource contexts.

Data availability

All data generated or analysed during this study are included in this published article [and its supplementary information files].

Abbreviations

Antimicrobial resistance

World Health Organization

United Nations Children’s Fund

International Prospective Register of Systematic Reviews

Preferred Reporting Items for Systematic Reviews and Meta-Analysis

Medical Subject Headings

Population, Intervention, Comparison, Outcomes, Study design/Setting

Joanna Briggs Institute

Grading of Recommendations Assessment, Development and Evaluation

Acute Respiratory Tract Infection

Patent and Proprietary Medicine Vendors

Theory of Planned Behaviour

Self-Determination Theory

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Acknowledgements

SM would also like to acknowledge the support of the Commonwealth through an Australian Government Research Training Program Scholarship.

This study was part of a PhD study, funded by the Australian Government Research Training Program Scholarship. The funding source had no input into the design of the study, the collection, analysis or interpretation of the data or the writing of the manuscript.

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This study was designed in collaboration between SM, MB and SP. SM completed the conceptual development, study design, data collection and analysis under the guidance and visualisation of MB and SP. MB and SP checked SM’s decisions at each stage of the review, participated in critically appraising studies, and oversaw data analysis. Discrepancies were resolved through regular team discussion and consultation. SM drafted the manuscript and MB and SP reviewed, modified and approved the final version.

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MB is co-founder of the Wollongong Antimicrobial Resistance Research Alliance (WARRA) [ 57 ] and has authored several publications traversing issues in AMR. MB is Adjunct Associate Professor with the School of Psychology at the University of Wollongong. SP is a Psychology Lecturer and the Course Coordinator of Psychology Honours, and has authored several systematic reviews. SM is a PhD Student and a Registered Psychologist with experience in Health Psychology.

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Marsh, S.A., Parsafar, S. & Byrne, M.K. Should my child be given antibiotics? A systematic review of parental decision making in rural and remote locations. Antimicrob Resist Infect Control 13 , 105 (2024). https://doi.org/10.1186/s13756-024-01409-1

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DOI : https://doi.org/10.1186/s13756-024-01409-1

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The Four Types of Research Paradigms: A Comprehensive Guide

Introduction to Research Paradigms

Three Pillars: Ontology, Epistemology, and Methodology

1. Positivist Research Paradigm

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4. Constructivist Research Paradigm

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Using Two Paradigms

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Should my child be given antibiotics? A systematic review of parental decision making in rural and remote locations