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How to Write a Comparative Analysis: A Step-by-Step Guide

Comparative analysis is a skill required in many academic and professional settings, yet often people struggle with how to approach it. In this guide, we will provide a step-by-step process for writing a successful comparative analysis. Whether you need to compare two theories, two pieces of literature, or two companies, this guide will help you structure your analysis in a clear and organized way.

Understanding Comparative Analysis

Definition and purpose of comparative analysis.

Comparative analysis is a valuable tool for gaining a deeper understanding of a topic. By comparing two or more things, we can identify their similarities and differences and draw meaningful conclusions from the comparison. The purpose of comparative analysis is to provide insight into the subject matter and to help us make informed decisions.

For example, a company may use comparative analysis to evaluate the performance of two different products. By comparing the sales figures, customer feedback, and other relevant data, the company can determine which product is more successful and make informed decisions about future product development.

Types of Comparative Analysis

There are several types of comparative analysis, each with its own unique methodology:

• Qualitative Comparative Analysis (QCA): This type of analysis is used to identify the factors that contribute to a particular outcome. QCA involves comparing cases that have similar outcomes but different factors to determine which factors are most important.
• Quantitative Comparative Analysis (QCA): This type of analysis involves comparing numerical data to identify patterns and relationships between variables. QCA can be used to evaluate the effectiveness of different treatments or interventions.
• Historical Comparative Analysis: This type of analysis involves comparing historical events or periods to identify similarities and differences. Historical comparative analysis can help us understand how societies and cultures have evolved over time.
• Textual Comparative Analysis: This type of analysis involves comparing texts to identify similarities and differences in language, themes, and other elements. Textual comparative analysis can help us understand how literature and other forms of media have evolved over time.

Each type of comparative analysis has its own strengths and weaknesses, and the choice of methodology will depend on the research question and the available data.

Overall, comparative analysis is a powerful tool for gaining insight into a wide range of topics. By comparing two or more things, we can identify patterns, relationships, and other important insights that can inform our decision-making and help us better understand the world around us.

Preparing for Your Comparative Analysis

Comparative analysis is a method of analyzing and comparing two or more things to gain a better understanding of them. It involves identifying similarities and differences between the subjects and drawing conclusions based on those observations. Here are some important steps to follow when preparing for your comparative analysis.

Selecting the Subjects for Comparison

The first step in preparing for your comparative analysis is to select the subjects for comparison. This may seem obvious, but it is important to carefully consider your choices. You should choose subjects that are similar in some way, yet different enough to make the comparison meaningful. For example, if you are comparing two cars, you might choose two cars of the same make and model but with different features.

It is also important to consider the scope of your analysis. Are you comparing two specific instances or are you comparing a broader category of things? This will help you to determine the level of detail you need to go into and the amount of research required.

Identifying the Basis for Comparison

Once you have selected your subjects, the next step is to identify the basis for comparison. This is the criteria against which you will be comparing the subjects. For example, if you are comparing two companies, you might choose to compare their financial performance or their marketing strategies.

It is important to choose a basis for comparison that is relevant to your research question and provides meaningful insights. You should also consider the availability and reliability of data for your chosen basis of comparison.

Conducting Preliminary Research

Before you begin your analysis, it is important to conduct some preliminary research on your subjects. This will help you to gain a better understanding of the similarities and differences between them and will inform your basis for comparison. You should look for information on the history, background, and characteristics of your subjects.

You can conduct your research using a variety of sources, including books, articles, and online databases. You should also consider conducting interviews with experts in the field or people who have experience with the subjects you are analyzing.

Overall, conducting thorough preliminary research will help you to develop a deeper understanding of your subjects and provide a foundation for your comparative analysis.

Developing a Thesis Statement

Importance of a strong thesis.

A thesis statement is the backbone of your comparative analysis. It is the main point that you will be making in your analysis. A strong thesis statement is important because it helps to guide your analysis and ensures that you stay focused on the main point. A weak thesis statement, on the other hand, can lead to a disorganized and unclear analysis.

Tips for Crafting a Thesis Statement

In order to craft a strong thesis statement, you should consider the following:

• Your basis for comparison
• The similarities and differences between your subjects
• Your overall conclusion

Your thesis statement should clearly state the main point that you will be making in your analysis and should be specific enough to guide your analysis.

Creating an Outline

Organizing your comparison.

Once you have developed your thesis statement, the next step is to create an outline for your analysis. Your outline should clearly identify the main points that you will be making and should be organized in a logical and coherent way. You should also consider the best way to present your comparison, whether that be through a side-by-side comparison or a point-by-point analysis.

Choosing a Structure for Your Analysis

When it comes to organizing your analysis, there are several different structures that you can choose from. Two of the most common structures are the block structure and the point-by-point structure. The block structure involves presenting all the information about one subject first, followed by the information about the second subject. The point-by-point structure involves comparing and contrasting the subjects on a point-by-point basis, drawing out the similarities and differences as you go.

Writing the Introduction

Introducing the subjects.

The introduction to your comparative analysis should provide some background information on the subjects that you are comparing. This may include a brief overview of their histories, their main characteristics, or their significance within their respective fields.

Presenting the Thesis Statement

Your introduction should also include your thesis statement, which should clearly state the main point that you will be making in your analysis. Your thesis statement should be concise and specific, and should guide the reader through your analysis.

By following these step-by-step guidelines, you can write a successful comparative analysis that is clear, organized, and persuasive. Remember to carefully consider your subjects, identify your basis for comparison, and craft a strong thesis statement. With these elements in place, you will be well on your way to a successful analysis.

ChatGPT Prompt for Writing a Comparative Analysis

Chatgpt prompt.

Compose a detailed and thorough examination that compares and contrasts two or more subjects, highlighting their similarities and differences. The analysis should provide a comprehensive evaluation of the subjects, including their strengths and weaknesses, with the goal of presenting a well-rounded and insightful perspective on the topic.

[ADD ADDITIONAL CONTEXT. CAN USE BULLET POINTS.]

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• > The Research Imagination
• > COMPARATIVE RESEARCH METHODS

Book contents

• Frontmatter
• 1 RESEARCH PROCESS
• 2 THEORY AND METHOD
• 3 RESEARCH DESIGN
• 4 MEASUREMENT
• 5 ETHICAL AND POLITICAL ISSUES
• 7 SURVEY RESEARCH
• 8 INTENSIVE INTERVIEWING
• 9 OBSERVATIONAL FIELD RESEARCH
• 10 FEMINIST METHODS
• 11 HISTORICAL ANALYSIS
• 12 EXPERIMENTAL RESEARCH
• 13 CONTENT ANALYSIS
• 14 AGGREGATE DATA ANALYSIS
• 15 COMPARATIVE RESEARCH METHODS
• 16 EVALUATION RESEARCH
• 17 INDEXES AND SCALES
• 18 BASIC STATISTICAL ANALYSIS
• 19 MULTIVARIATE ANALYSIS AND STATISTICAL SIGNIFICANCE
• EPILOGUE: THE VALUE AND LIMITS OF SOCIAL SCIENCE KNOWLEDGE
• Appendix A A Precoded Questionnaire
• Appendix B Excerpt from a Codebook
• Author Index
• Subject Index

15 - COMPARATIVE RESEARCH METHODS

Published online by Cambridge University Press:  05 June 2012

INTRODUCTION

In contrast to the chapters on survey research, experimentation, or content analysis that described a distinct set of skills, in this chapter, a variety of comparative research techniques are discussed. What makes a study comparative is not the particular techniques employed but the theoretical orientation and the sources of data. All the tools of the social scientist, including historical analysis, fieldwork, surveys, and aggregate data analysis, can be used to achieve the goals of comparative research. So, there is plenty of room for the research imagination in the choice of data collection strategies. There is a wide divide between quantitative and qualitative approaches in comparative work. Most studies are either exclusively qualitative (e.g., individual case studies of a small number of countries) or exclusively quantitative, most often using many cases and a cross-national focus (Ragin, 1991:7). Ideally, increasing numbers of studies in the future will use both traditions, as the skills, tools, and quality of data in comparative research continue to improve.

In almost all social research, we look at how social processes vary and are experienced in different settings to develop our knowledge of the causes and effects of human behavior. This holds true if we are trying to explain the behavior of nations or individuals. So, it may then seem redundant to include a chapter in this book specifically dedicated to comparative research methods when all the other methods discussed are ultimately comparative.

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• COMPARATIVE RESEARCH METHODS
• Paul S. Gray , Boston College, Massachusetts , John B. Williamson , Boston College, Massachusetts , David A. Karp , Boston College, Massachusetts , John R. Dalphin
• Book: The Research Imagination
• Online publication: 05 June 2012
• Chapter DOI: https://doi.org/10.1017/CBO9780511819391.016

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How to Do Comparative Analysis in Research ( Examples )

Comparative analysis is a method that is widely used in social science . It is a method of comparing two or more items with an idea of uncovering and discovering new ideas about them. It often compares and contrasts social structures and processes around the world to grasp general patterns. Comparative analysis tries to understand the study and explain every element of data that comparing. 

Most social scientists are involved in comparative analysis. Macfarlane has thought that “On account of history, the examinations are typically on schedule, in that of other sociologies, transcendently in space. The historian always takes their society and compares it with the past society, and analyzes how far they differ from each other.

The comparative method of social research is a product of 19 th -century sociology and social anthropology. Sociologists like Emile Durkheim, Herbert Spencer Max Weber used comparative analysis in their works. For example, Max Weber compares the protestant of Europe with Catholics and also compared it with other religions like Islam, Hinduism, and Confucianism.

To do a systematic comparison we need to follow different elements of the method.

In social science, we can do comparisons in different ways. It is merely different based on the topic, the field of study. Like Emile Durkheim compare societies as organic solidarity and mechanical solidarity. The famous sociologist Emile Durkheim provides us with three different approaches to the comparative method. Which are;

3. The motive of comparison

As another method of study, a comparative analysis is one among them for the social scientist. The researcher or the person who does the comparative method must know for what grounds they taking the comparative method. They have to consider the strength, limitations, weaknesses, etc. He must have to know how to do the analysis.

Steps of the comparative method

As mentioned earlier, the first step is to consider and determine the unit of comparison for your study. You must consider all the dimensions of your unit. This is where you put the two things you need to compare and to properly analyze and compare it. It is not an easy step, we have to systematically and scientifically do this with proper methods and techniques. You have to build your objectives, variables and make some assumptions or ask yourself about what you need to study or make a hypothesis for your analysis.

The grounds of comparison should be understandable for the reader. You must acknowledge why you selected these units for your comparison. For example, it is quite natural that a person who asks why you choose this what about another one? What is the reason behind choosing this particular society? If a social scientist chooses primitive Asian society and primitive Australian society for comparison, he must acknowledge the grounds of comparison to the readers. The comparison of your work must be self-explanatory without any complications.

The main element of the comparative analysis is the thesis or the report. The report is the most important one that it must contain all your frame of reference. It must include all your research questions, objectives of your topic, the characteristics of your two units of comparison, variables in your study, and last but not least the finding and conclusion must be written down. The findings must be self-explanatory because the reader must understand to what extent did they connect and what are their differences. For example, in Emile Durkheim’s Theory of Division of Labour, he classified organic solidarity and Mechanical solidarity . In which he means primitive society as Mechanical solidarity and modern society as Organic Solidarity. Like that you have to mention what are your findings in the thesis.

Your paper must link each point in the argument. Without that the reader does not understand the logical and rational advance in your analysis. In a comparative analysis, you need to compare the ‘x’ and ‘y’ in your paper. (x and y mean the two-unit or things in your comparison). To do that you can use likewise, similarly, on the contrary, etc. For example, if we do a comparison between primitive society and modern society we can say that; ‘in the primitive society the division of labour is based on gender and age on the contrary (or the other hand), in modern society, the division of labour is based on skill and knowledge of a person.

Demerits of comparison

Comparative analysis is not always successful. It has some limitations. The broad utilization of comparative analysis can undoubtedly cause the feeling that this technique is a solidly settled, smooth, and unproblematic method of investigation, which because of its undeniable intelligent status can produce dependable information once some specialized preconditions are met acceptably.

One more basic issue with broad ramifications concerns the decision of the units being analyzed. The primary concern is that a long way from being a guiltless as well as basic assignment, the decision of comparison units is a basic and precarious issue. The issue with this sort of comparison is that in such investigations the depictions of the cases picked for examination with the principle one will in general turn out to be unreasonably streamlined, shallow, and stylised with contorted contentions and ends as entailment.

However, a comparative analysis is as yet a strategy with exceptional benefits, essentially due to its capacity to cause us to perceive the restriction of our psyche and check against the weaknesses and hurtful results of localism and provincialism. We may anyway have something to gain from history specialists’ faltering in utilizing comparison and from their regard for the uniqueness of settings and accounts of people groups. All of the above, by doing the comparison we discover the truths the underlying and undiscovered connection, differences that exist in society.

How to Write a Comparative Analysis Dissertation: Useful Guidelines

Writing a dissertation involves more than just demonstrating your expertise in your chosen field of study. It also requires using important skills, such as analytical thinking. Without it, developing sound theories, introducing arguments, or making conclusions would be impossible. And nowhere is this ability more prominently showcased than in writing comparative analysis dissertations.

Comparative analysis is a helpful method you can use to do research. Remember writing compare-and-contrast essays at school? It’s actually very similar to conducting this type of analysis. But it also has plenty of peculiarities that make it a unique approach. Keep reading to learn more about it!

What Is a Comparative Analysis Dissertation?

Comparative analysis types.

• Possible Difficulties
• Elements of Comparative Analysis
• How to Write a Comparative Analysis Dissertation

Comparative analysis boils down to studying similarities and differences between two or more things, be it theories, texts, processes, personalities, or time periods. This method is especially useful in conducting social sciences , humanities, history, and business research.

Conducting a comparative analysis helps you achieve multiple goals:

• It allows you to find parallels and dissimilaritie s between your subjects and use them to make broader conclusions.
• Putting two or more things against each other also helps to see them in a new light and notice the usually neglected aspects.
• In addition to similarities and differences, conducting a comparative analysis helps to determine causality —that is, the reason why these characteristics exist in the first place.

Depending on your research methods, your comparative analysis dissertation can be of two types:

• Qualitative comparative analysis revolves around individual examples. It uses words and concepts to describe the subjects of comparison and make conclusions from them. Essentially, it’s about studying a few examples closely to understand their specific details. This method will be especially helpful if you’re writing a comparative case study dissertation.
• Quantitative comparative dissertations will use numbers and statistics to explain things. It helps make general statements about big sample groups. You will usually need a lot of examples to gather plenty of reliable numerical data for this kind of research.

There are no strict rules regarding these types. You can use the features of both in your comparative dissertation if you want to.

Possible Difficulties of Writing a Comparative Analysis Dissertation

As you can see, comparison is an excellent research method that can be a great help in dissertation writing . But it also has its drawbacks and challenges. It’s essential to be aware of them and do your best to overcome them:

• Your chosen subjects of comparison may have very little in common . In that case, it might be tricky to come up with at least some similarities.
• Sometimes, there may not be enough information about the things you want to study. This will seriously limit your choices and may affect the accuracy of your research results. To avoid it, we recommend you choose subjects you’re already familiar with.
• Choosing a small number of cases or samples will make it much more challenging to generalize your findings . It may also cause you to overlook subtle ways in which the subjects influence each other. That’s why it’s best to choose a moderate number of items from which to draw comparisons, usually between 5 and 40.
• It’s also essential that your dissertation looks different from a s high school compare-and-contrast essay. Instead, your work should be appropriately structured. Read on to learn how to do it!

Elements of Dissertation Comparative Analysis

Do you want your dissertation comparative analysis to be successful? Then make sure it has the following key elements:

• Context Your comparative dissertation doesn’t exist in a vacuum. It has historical and theoretical contexts as well as previous research surrounding it. You can cover these aspects in your introduction and literature review .
• Goals It should be clear to the reader why you want to compare two particular things. That’s why, before you start making your dissertation comparative analysis, you’ll need to explain your goal. For example, the goal of a dissertation in human science can be to describe and classify something.
• Modes of Comparison This refers to the way you want to conduct your research. There are four modes of comparison to choose from: similarity-focused, difference-focused, genus-species relationship, and refocusing.

• Scale This is the degree to which your study will be zooming on the subjects of comparison. It’s similar to looking at maps. There are maps of the entire world, of separate countries, and of smaller locations. The scale of your research refers to how detailed the map is. You will need to use similar scale maps for each subject to conduct a good comparison.
• Scope This criterion refers to how far removed your subjects are in time and space. Depending on the scope, there are two types of comparisons:

• Research Question This is the key inquiry that guides your entire study. In a comparative analysis thesis, the research question usually addresses similarities and differences, but it can also focus on other patterns you’ll be exploring. It can belong to one of the following types, depending on the kind of analysis you want to apply:

Want to write your research question quickly and easily? Try our thesis statement generator ! It has four modes depending on your type of writing, which helps it produce customized results.

• Data Analysis Here, you analyze similarities, differences, and relationships you’ve identified between the subjects. Make sure to provide your argumentation and explain where your findings come from.
• Conclusions This element addresses the research question and answers it. It can also point out the significance of similarities and differences that you’ve found.

How to Write a Comparative Analysis Dissertation

Now that you know what your comparative analysis should include, it’s time to learn how to write it! Follow the steps, and you’ll be sure to succeed:

• Select the Subjects This is the most critical step on which your entire dissertation will depend. To choose things to compare, try to analyze several important factors, including your potential audience , the overall goal of the study, and your interests. It’s also essential to check whether the things you want to discuss are sufficiently studied. While you research possible topics, you may stumble upon untrustworthy AI-generated content. Unfortunately, it’s getting increasingly difficult to differentiate it from human-made writing. To avoid getting into this trap, consider using an AI detection tool . It provides 100% accurate results and is completely free.
• Describe Your Chosen Items Before you can start comparing the subjects, it’s necessary to describe them in their social and historical contexts. Without taking a long, hard look at your topic’s background, it would be impossible to determine what you should pay attention to during your research. To describe your subjects properly, you will need to study plenty of sources and convey their content in your dissertation. Want to simplify this task? Check out our excellent free summarizer tool !
• Juxtapose Now, it’s time to do the comparison by checking how similar and different your subjects are. Some may think focusing on the resemblances is more critical, while others find contrasts more exciting. Both these viewpoints are valid, but the best approach is to find the right balance depending on your study’s goal.
• Provide Redescription Unlike previous steps, this one is optional. It involves looking at something for the second time after conducting the comparison. The point is that you might learn new things about your subjects during your study. They may even help shed light on each other (it’s called “ reciprocal illumination .”) This knowledge will likely deepen your understanding or even change it altogether. It’s a good idea to point it out in your comparative case study dissertation.
• Consider Rectification and Theory Formation These two processes are also optional. They involve upgrading your writing and theories after conducting your research. This doesn’t mean changing the topic of you study. Instead, it refers to changing how you think about your subjects. For example, you may gain some new understanding and realize that you weren’t using the right words to properly describe your subjects. That’s when rectification comes into play. Essentially, you revise the language used in your discussion to make it more precise and appropriate. This new perspective may even inspire you to come up with a new theory about your topic! In that case, you may write about it, too. Usually, though, rectification is enough. If you decide to do it, feel free to use our paraphrasing tool to help you find the right words.
• Edit and Proofread After you’re done writing the bulk of your text, it’s essential to check it and ensure it passes the plagiarism check. After all, even if you haven’t directly copied other people’s texts, there may still be some percentage of accidental plagiarism that can get you in trouble. To ensure that it doesn’t happen, use our free plagiarism detector .

And this is how you write a comparative analysis dissertation! We hope our tips will be helpful to you. Read our next article if you need help with a  literature review in a dissertation . Good luck with your studies!

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How to write a comparative analysis.

Writing a comparative review in a research paper is not as difficult as many people might tend to think. With some tips, it is possible to write an outstanding comparative review. There are steps that must be utilized to attain this result. They are as detailed in this article.

Within the literary, academic, and journalistic world, analysis allows exposing ideas and arguments in front of a context, making it an important material for discussion within the professional work.

Within this genre, we can find a comparative analysis. For some authors, the comparative essay is defined as the text where two opposing positions are proposed or where two theses are verified. Through this comparison, the author intends to make the reader reflect on a specific topic. It consists of giving a written opinion about two positions, which are compared between them to conclude. Do you know how to write a comparative essay? In this article, we will explain step by step how to do it.

So, let’s see the guidelines that you must follow to achieve a good comparative analysis .

How to write a good comparative analysis

The structure.

In general, the approach is developed in the first paragraph or at the beginning of the work. Its objective is to propose the author’s position regarding a specific subject. Generally, this approach specifies the objective to be achieved. You must be clear about what topic you are going to deal with, what you want to explain, and what the perspectives will be to use in your comparative analysis, and you must also define who you write for.

As it is a comparative text, it begins with a general observation that can serve as a context for both approaches, then begins by establishing the arguments in each of the two cases. Do not forget to compare both objects of study according to each argument or idea to develop.

Let it be the reader himself who finds or defines his position in this essay and choose one of the two alternatives.

In this entry, there are two possibilities of approach: one deductive and the other inductive. The deductive method raises the issue, and you use your analysis of the variables leading, guiding the reader to draw their conclusions or fix a position on the issue. While the inductive method starts with argument, developing each of the variables until reaching the topic’s approach or problem. The two ways of approaching the subject are viable. Choose the one that is easiest for you to work with.

At the end of this section, your audience should:

• First of all, have a clear understanding of what topics you will cover in your essay, what you want to explain, and under what positions or perspectives you will do it. It begins with a general observation that establishes the similarity between the two subjects and then moves the essay’s focus to the concrete.
• The reader should understand which points will be examined and which points will not be examined in the comparison. At the end of the introduction, state your preference, or describe the two subjects’ meaning.
• Your readers should be able to describe the ideas you are going to treat. Make a detailed exposition of its characteristics, history, consequences, and development that you consider appropriate. Your comparative analysis should expose the characteristics of the second position on which you want to speak as much as in the first one.

Development of body

Generally, in the body of the essay, the author presents all the arguments that support his thesis, which gives him a reflective and justifying body of the author’s initial statement. Depending on the length of the work, which can range from two to 15 pages, each paragraph or before a title corresponds to an argument’s development.

After speaking on the subject, the author must close the essay, must conclude, must show the findings of his work, and/or show the conclusions he reached. You must write a final closing paragraph, as a conclusion, in which you expose a confrontation between the two positions. Try to create a fight between them so that the reader gets involved. The conclusion should give a brief and general summary of the most important similarities and differences. It should end with a personal statement, an opinion, and the “what then?” – what is important about the two things being compared.

Readers should be left feeling that all the different threads of this essay have been put together coherently, that they have learned something – and they must be sure that this is the end – that they do not look around for pages missing. And finally, your assessment must explain what position you stand in solidarity and why you prefer it to the other.

Examples of how to write a comparative analysis

Paragraph 1: Messi’s preferred position / Ronaldo’s preferred position.

Paragraph 2: Messi’s play style / Ronaldo’s play style.

Paragraph 3: Messi aerial game / Ronaldo aerial game.

Paragraph 1: Messi teamwork .

Paragraph 2: Ronaldo’s teamwork.

Paragraph 3: Messi stopped the ball.

Paragraph 4: Ronaldo’s stopped the ball.

Paragraph 5: Messi’s achievements.

Paragraph 6: Ronaldo’s achievements.

Few Important Rules for Comparative analysis

Even if the exercise sounds simple, there are a few rules that should be followed to help your audience as best as possible make the best decision.

1. Clearly state your position

The first question is, “Why are you doing a comparison analysis”? To highlight your view or ideas over another, or simply to compare two (or more) solutions that do not belong to you? It is imperative that you clearly state your position to your reader, so does your credibility.

Be honest and state, for example:

• The idea you are trying to espouse
• The framework you are using
• The reason why you are doing this comparison, the objective

In addition to the above, you must be consistent with the exposition of your ideas.

2. Stay objective

Even if you include your personal ideology in your comparison, stay as objective as possible. Your readers will not appreciate it when you point out all the disadvantages of one idea while you display the advantages of the other. Your comparison will turn into advertising. You have to raise weak points and strong points on both sides.

These analyses are always subjective, so you have to clarify which position convinces you the most.

3. Think about audience’ expectations

The research paper is intended for your readers, which means that you must take their expectations into account when writing your review. Put aside your desire to sell your desired idea, and take your readers’ perspective:

• What information are they interested in?
• What are their criteria?
• What do they want to know?
• What do they want from the product or service?

Again, it is about being objective in all your statements.

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4. Organize information

For your readers to want to read your comparative analysis, it is important to structure your comments. The idea is to make it easy for your readers to navigate your paper and get them to find the information that interests them quickly.

5. End with a conclusion

You’ve tried to be as objective as possible throughout your comparison, and now is the time to let go like we have mentioned many times in this post. In your conclusion, you can go directly to your readers and give your opinion. With a few tips, you can also encourage them to go towards one or the other idea.

Note: If time is not an issue, the best way to review the essay is to leave it for one day. Go for a walk, eat something, have fun, and forget. Then it’s time to go back to the text, find problems, and fix them. This must be done separately, that is, first find all the problems you can without correcting them. Although the idea of ​​doing it at the same time is tempting, it is smarter to do it separately. It is effective and fast.

Tips on Comparative analysis

Be concise or accurate in your analysis and dissertation of the topic.

Sometimes the authors believe that the more elaborate the language and the more extensive the writing, the better the writers or essayists. On the contrary, a good essay refers to the exact analysis of a topic, where the reader can dynamically advance the work and understand the author’s position.

Use only the arguments necessary for the explanation of the topic, do not talk too much. You run the risk of redundant or repetitive, which makes the text-heavy both when reading it and understanding it.

Write in Short Sentences

Just as we recommend that you do not redound in your texts, we also encourage you to write with short sentences. They give dynamism to the text. Communication is direct. The reader advances in the text and understands much more.

Include Reflections in Your Text

Supporting your approach with reflections or quotes from authors makes your essay more important. Above all, use those arguments that justify or give strength to your position regarding one thesis or the other.

Text Revision

Since comparative analysis can tend to be a subjective work, you must let it “sit” for a day or a few hours and read it again. This exercise will allow you to make corrections. Modify those aspects that are not clear enough for you. And you can improve it, in a few words. Once you do this exercise, just like this, you can submit it.

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Characteristics of a Comparative Research Design

Hannah richardson, 28 jun 2018.

Comparative research essentially compares two groups in an attempt to draw a conclusion about them. Researchers attempt to identify and analyze similarities and differences between groups, and these studies are most often cross-national, comparing two separate people groups. Comparative studies can be used to increase understanding between cultures and societies and create a foundation for compromise and collaboration. These studies contain both quantitative and qualitative research methods.

Explore this article

• Comparative Quantitative
• Comparative Qualitative
• When to Use It
• When Not to Use It

1 Comparative Quantitative

Quantitative, or experimental, research is characterized by the manipulation of an independent variable to measure and explain its influence on a dependent variable. Because comparative research studies analyze two different groups -- which may have very different social contexts -- it is difficult to establish the parameters of research. Such studies might seek to compare, for example, large amounts of demographic or employment data from different nations that define or measure relevant research elements differently.

However, the methods for statistical analysis of data inherent in quantitative research are still helpful in establishing correlations in comparative studies. Also, the need for a specific research question in quantitative research helps comparative researchers narrow down and establish a more specific comparative research question.

2 Comparative Qualitative

Qualitative, or nonexperimental, is characterized by observation and recording outcomes without manipulation. In comparative research, data are collected primarily by observation, and the goal is to determine similarities and differences that are related to the particular situation or environment of the two groups. These similarities and differences are identified through qualitative observation methods. Additionally, some researchers have favored designing comparative studies around a variety of case studies in which individuals are observed and behaviors are recorded. The results of each case are then compared across people groups.

3 When to Use It

Comparative research studies should be used when comparing two people groups, often cross-nationally. These studies analyze the similarities and differences between these two groups in an attempt to better understand both groups. Comparisons lead to new insights and better understanding of all participants involved. These studies also require collaboration, strong teams, advanced technologies and access to international databases, making them more expensive. Use comparative research design when the necessary funding and resources are available.

4 When Not to Use It

Do not use comparative research design with little funding, limited access to necessary technology and few team members. Because of the larger scale of these studies, they should be conducted only if adequate population samples are available. Additionally, data within these studies require extensive measurement analysis; if the necessary organizational and technological resources are not available, a comparative study should not be used. Do not use a comparative design if data are not able to be measured accurately and analyzed with fidelity and validity.

• 1 San Jose State University: Selected Issues in Study Design
• 2 University of Surrey: Social Research Update 13: Comparative Research Methods

About the Author

Hannah Richardson has a Master's degree in Special Education from Vanderbilt University and a Bacheor of Arts in English. She has been a writer since 2004 and wrote regularly for the sports and features sections of "The Technician" newspaper, as well as "Coastwach" magazine. Richardson also served as the co-editor-in-chief of "Windhover," an award-winning literary and arts magazine. She is currently teaching at a middle school.

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• Comparative Analysis

What It Is and Why It's Useful

Comparative analysis asks writers to make an argument about the relationship between two or more texts. Beyond that, there's a lot of variation, but three overarching kinds of comparative analysis stand out:

• Coordinate (A ↔ B): In this kind of analysis, two (or more) texts are being read against each other in terms of a shared element, e.g., a memoir and a novel, both by Jesmyn Ward; two sets of data for the same experiment; a few op-ed responses to the same event; two YA books written in Chicago in the 2000s; a film adaption of a play; etc. 
• Subordinate (A  → B) or (B → A ): Using a theoretical text (as a "lens") to explain a case study or work of art (e.g., how Anthony Jack's The Privileged Poor can help explain divergent experiences among students at elite four-year private colleges who are coming from similar socio-economic backgrounds) or using a work of art or case study (i.e., as a "test" of) a theory's usefulness or limitations (e.g., using coverage of recent incidents of gun violence or legislation un the U.S. to confirm or question the currency of Carol Anderson's The Second ).
• Hybrid [A  → (B ↔ C)] or [(B ↔ C) → A] , i.e., using coordinate and subordinate analysis together. For example, using Jack to compare or contrast the experiences of students at elite four-year institutions with students at state universities and/or community colleges; or looking at gun culture in other countries and/or other timeframes to contextualize or generalize Anderson's main points about the role of the Second Amendment in U.S. history.

"In the wild," these three kinds of comparative analysis represent increasingly complex—and scholarly—modes of comparison. Students can of course compare two poems in terms of imagery or two data sets in terms of methods, but in each case the analysis will eventually be richer if the students have had a chance to encounter other people's ideas about how imagery or methods work. At that point, we're getting into a hybrid kind of reading (or even into research essays), especially if we start introducing different approaches to imagery or methods that are themselves being compared along with a couple (or few) poems or data sets.

Why It's Useful

In the context of a particular course, each kind of comparative analysis has its place and can be a useful step up from single-source analysis. Intellectually, comparative analysis helps overcome the "n of 1" problem that can face single-source analysis. That is, a writer drawing broad conclusions about the influence of the Iranian New Wave based on one film is relying entirely—and almost certainly too much—on that film to support those findings. In the context of even just one more film, though, the analysis is suddenly more likely to arrive at one of the best features of any comparative approach: both films will be more richly experienced than they would have been in isolation, and the themes or questions in terms of which they're being explored (here the general question of the influence of the Iranian New Wave) will arrive at conclusions that are less at-risk of oversimplification.

For scholars working in comparative fields or through comparative approaches, these features of comparative analysis animate their work. To borrow from a stock example in Western epistemology, our concept of "green" isn't based on a single encounter with something we intuit or are told is "green." Not at all. Our concept of "green" is derived from a complex set of experiences of what others say is green or what's labeled green or what seems to be something that's neither blue nor yellow but kind of both, etc. Comparative analysis essays offer us the chance to engage with that process—even if only enough to help us see where a more in-depth exploration with a higher and/or more diverse "n" might lead—and in that sense, from the standpoint of the subject matter students are exploring through writing as well the complexity of the genre of writing they're using to explore it—comparative analysis forms a bridge of sorts between single-source analysis and research essays.

Typical learning objectives for single-sources essays: formulate analytical questions and an arguable thesis, establish stakes of an argument, summarize sources accurately, choose evidence effectively, analyze evidence effectively, define key terms, organize argument logically, acknowledge and respond to counterargument, cite sources properly, and present ideas in clear prose.

Common types of comparative analysis essays and related types: two works in the same genre, two works from the same period (but in different places or in different cultures), a work adapted into a different genre or medium, two theories treating the same topic; a theory and a case study or other object, etc.

How to Teach It: Framing + Practice

Framing multi-source writing assignments (comparative analysis, research essays, multi-modal projects) is likely to overlap a great deal with "Why It's Useful" (see above), because the range of reasons why we might use these kinds of writing in academic or non-academic settings is itself the reason why they so often appear later in courses. In many courses, they're the best vehicles for exploring the complex questions that arise once we've been introduced to the course's main themes, core content, leading protagonists, and central debates.

For comparative analysis in particular, it's helpful to frame assignment's process and how it will help students successfully navigate the challenges and pitfalls presented by the genre. Ideally, this will mean students have time to identify what each text seems to be doing, take note of apparent points of connection between different texts, and start to imagine how those points of connection (or the absence thereof)

• complicates or upends their own expectations or assumptions about the texts
• complicates or refutes the expectations or assumptions about the texts presented by a scholar
• confirms and/or nuances expectations and assumptions they themselves hold or scholars have presented
• presents entirely unforeseen ways of understanding the texts

—and all with implications for the texts themselves or for the axes along which the comparative analysis took place. If students know that this is where their ideas will be heading, they'll be ready to develop those ideas and engage with the challenges that comparative analysis presents in terms of structure (See "Tips" and "Common Pitfalls" below for more on these elements of framing).

Like single-source analyses, comparative essays have several moving parts, and giving students practice here means adapting the sample sequence laid out at the " Formative Writing Assignments " page. Three areas that have already been mentioned above are worth noting:

• Gathering evidence : Depending on what your assignment is asking students to compare (or in terms of what), students will benefit greatly from structured opportunities to create inventories or data sets of the motifs, examples, trajectories, etc., shared (or not shared) by the texts they'll be comparing. See the sample exercises below for a basic example of what this might look like.
• Why it Matters: Moving beyond "x is like y but also different" or even "x is more like y than we might think at first" is what moves an essay from being "compare/contrast" to being a comparative analysis . It's also a move that can be hard to make and that will often evolve over the course of an assignment. A great way to get feedback from students about where they're at on this front? Ask them to start considering early on why their argument "matters" to different kinds of imagined audiences (while they're just gathering evidence) and again as they develop their thesis and again as they're drafting their essays. ( Cover letters , for example, are a great place to ask writers to imagine how a reader might be affected by reading an their argument.)
• Structure: Having two texts on stage at the same time can suddenly feel a lot more complicated for any writer who's used to having just one at a time. Giving students a sense of what the most common patterns (AAA / BBB, ABABAB, etc.) are likely to be can help them imagine, even if provisionally, how their argument might unfold over a series of pages. See "Tips" and "Common Pitfalls" below for more information on this front.

Sample Exercises and Links to Other Resources

• Common Pitfalls
• Advice on Timing
• Try to keep students from thinking of a proposed thesis as a commitment. Instead, help them see it as more of a hypothesis that has emerged out of readings and discussion and analytical questions and that they'll now test through an experiment, namely, writing their essay. When students see writing as part of the process of inquiry—rather than just the result—and when that process is committed to acknowledging and adapting itself to evidence, it makes writing assignments more scientific, more ethical, and more authentic. 
• Have students create an inventory of touch points between the two texts early in the process.
• Ask students to make the case—early on and at points throughout the process—for the significance of the claim they're making about the relationship between the texts they're comparing.
• For coordinate kinds of comparative analysis, a common pitfall is tied to thesis and evidence. Basically, it's a thesis that tells the reader that there are "similarities and differences" between two texts, without telling the reader why it matters that these two texts have or don't have these particular features in common. This kind of thesis is stuck at the level of description or positivism, and it's not uncommon when a writer is grappling with the complexity that can in fact accompany the "taking inventory" stage of comparative analysis. The solution is to make the "taking inventory" stage part of the process of the assignment. When this stage comes before students have formulated a thesis, that formulation is then able to emerge out of a comparative data set, rather than the data set emerging in terms of their thesis (which can lead to confirmation bias, or frequency illusion, or—just for the sake of streamlining the process of gathering evidence—cherry picking). 
• For subordinate kinds of comparative analysis , a common pitfall is tied to how much weight is given to each source. Having students apply a theory (in a "lens" essay) or weigh the pros and cons of a theory against case studies (in a "test a theory") essay can be a great way to help them explore the assumptions, implications, and real-world usefulness of theoretical approaches. The pitfall of these approaches is that they can quickly lead to the same biases we saw here above. Making sure that students know they should engage with counterevidence and counterargument, and that "lens" / "test a theory" approaches often balance each other out in any real-world application of theory is a good way to get out in front of this pitfall.
• For any kind of comparative analysis, a common pitfall is structure. Every comparative analysis asks writers to move back and forth between texts, and that can pose a number of challenges, including: what pattern the back and forth should follow and how to use transitions and other signposting to make sure readers can follow the overarching argument as the back and forth is taking place. Here's some advice from an experienced writing instructor to students about how to think about these considerations:

a quick note on STRUCTURE

     Most of us have encountered the question of whether to adopt what we might term the “A→A→A→B→B→B” structure or the “A→B→A→B→A→B” structure.  Do we make all of our points about text A before moving on to text B?  Or do we go back and forth between A and B as the essay proceeds?  As always, the answers to our questions about structure depend on our goals in the essay as a whole.  In a “similarities in spite of differences” essay, for instance, readers will need to encounter the differences between A and B before we offer them the similarities (A d →B d →A s →B s ).  If, rather than subordinating differences to similarities you are subordinating text A to text B (using A as a point of comparison that reveals B’s originality, say), you may be well served by the “A→A→A→B→B→B” structure.  

     Ultimately, you need to ask yourself how many “A→B” moves you have in you.  Is each one identical?  If so, you may wish to make the transition from A to B only once (“A→A→A→B→B→B”), because if each “A→B” move is identical, the “A→B→A→B→A→B” structure will appear to involve nothing more than directionless oscillation and repetition.  If each is increasingly complex, however—if each AB pair yields a new and progressively more complex idea about your subject—you may be well served by the “A→B→A→B→A→B” structure, because in this case it will be visible to readers as a progressively developing argument.

As we discussed in "Advice on Timing" at the page on single-source analysis, that timeline itself roughly follows the "Sample Sequence of Formative Assignments for a 'Typical' Essay" outlined under " Formative Writing Assignments, " and it spans about 5–6 steps or 2–4 weeks. 

Comparative analysis assignments have a lot of the same DNA as single-source essays, but they potentially bring more reading into play and ask students to engage in more complicated acts of analysis and synthesis during the drafting stages. With that in mind, closer to 4 weeks is probably a good baseline for many single-source analysis assignments. For sections that meet once per week, the timeline will either probably need to expand—ideally—a little past the 4-week side of things, or some of the steps will need to be combined or done asynchronously.

What It Can Build Up To

Comparative analyses can build up to other kinds of writing in a number of ways. For example:

• They can build toward other kinds of comparative analysis, e.g., student can be asked to choose an additional source to complicate their conclusions from a previous analysis, or they can be asked to revisit an analysis using a different axis of comparison, such as race instead of class. (These approaches are akin to moving from a coordinate or subordinate analysis to more of a hybrid approach.)
• They can scaffold up to research essays, which in many instances are an extension of a "hybrid comparative analysis."
• Like single-source analysis, in a course where students will take a "deep dive" into a source or topic for their capstone, they can allow students to "try on" a theoretical approach or genre or time period to see if it's indeed something they want to research more fully.
• DIY Guides for Analytical Writing Assignments

• Types of Assignments
• Unpacking the Elements of Writing Prompts
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What is comparative analysis? A complete guide

Last updated

18 April 2023

Reviewed by

Jean Kaluza

Short on time? Get an AI generated summary of this article instead

Comparative analysis is a valuable tool for acquiring deep insights into your organization’s processes, products, and services so you can continuously improve them. 

Similarly, if you want to streamline, price appropriately, and ultimately be a market leader, you’ll likely need to draw on comparative analyses quite often.

When faced with multiple options or solutions to a given problem, a thorough comparative analysis can help you compare and contrast your options and make a clear, informed decision.

If you want to get up to speed on conducting a comparative analysis or need a refresher, here’s your guide.

Make comparative analysis less tedious

Dovetail streamlines comparative analysis to help you uncover and share actionable insights

• What exactly is comparative analysis?

A comparative analysis is a side-by-side comparison that systematically compares two or more things to pinpoint their similarities and differences. The focus of the investigation might be conceptual—a particular problem, idea, or theory—or perhaps something more tangible, like two different data sets.

For instance, you could use comparative analysis to investigate how your product features measure up to the competition.

After a successful comparative analysis, you should be able to identify strengths and weaknesses and clearly understand which product is more effective.

You could also use comparative analysis to examine different methods of producing that product and determine which way is most efficient and profitable.

The potential applications for using comparative analysis in everyday business are almost unlimited. That said, a comparative analysis is most commonly used to examine

Emerging trends and opportunities (new technologies, marketing)

Competitor strategies

Financial health

Effects of trends on a target audience

Free AI content analysis generator

Make sense of your research by automatically summarizing key takeaways through our free content analysis tool.

• Why is comparative analysis so important? 

Comparative analysis can help narrow your focus so your business pursues the most meaningful opportunities rather than attempting dozens of improvements simultaneously.

A comparative approach also helps frame up data to illuminate interrelationships. For example, comparative research might reveal nuanced relationships or critical contexts behind specific processes or dependencies that wouldn’t be well-understood without the research.

For instance, if your business compares the cost of producing several existing products relative to which ones have historically sold well, that should provide helpful information once you’re ready to look at developing new products or features.

• Comparative vs. competitive analysis—what’s the difference?

Comparative analysis is generally divided into three subtypes, using quantitative or qualitative data and then extending the findings to a larger group. These include

Pattern analysis —identifying patterns or recurrences of trends and behavior across large data sets.

Data filtering —analyzing large data sets to extract an underlying subset of information. It may involve rearranging, excluding, and apportioning comparative data to fit different criteria. 

Decision tree —flowcharting to visually map and assess potential outcomes, costs, and consequences.

In contrast, competitive analysis is a type of comparative analysis in which you deeply research one or more of your industry competitors. In this case, you’re using qualitative research to explore what the competition is up to across one or more dimensions.

For example

Service delivery —metrics like the Net Promoter Scores indicate customer satisfaction levels.

Market position — the share of the market that the competition has captured.

Brand reputation —how well-known or recognized your competitors are within their target market.

• Tips for optimizing your comparative analysis

Conduct original research

Thorough, independent research is a significant asset when doing comparative analysis. It provides evidence to support your findings and may present a perspective or angle not considered previously. 

Make analysis routine

To get the maximum benefit from comparative research, make it a regular practice, and establish a cadence you can realistically stick to. Some business areas you could plan to analyze regularly include:

Profitability

Competition

Experiment with controlled and uncontrolled variables

In addition to simply comparing and contrasting, explore how different variables might affect your outcomes.

For example, a controllable variable would be offering a seasonal feature like a shopping bot to assist in holiday shopping or raising or lowering the selling price of a product.

Uncontrollable variables include weather, changing regulations, the current political climate, or global pandemics.

Put equal effort into each point of comparison

Most people enter into comparative research with a particular idea or hypothesis already in mind to validate. For instance, you might try to prove the worthwhileness of launching a new service. So, you may be disappointed if your analysis results don’t support your plan.

However, in any comparative analysis, try to maintain an unbiased approach by spending equal time debating the merits and drawbacks of any decision. Ultimately, this will be a practical, more long-term sustainable approach for your business than focusing only on the evidence that favors pursuing your argument or strategy.

Writing a comparative analysis in five steps

To put together a coherent, insightful analysis that goes beyond a list of pros and cons or similarities and differences, try organizing the information into these five components:

1. Frame of reference

Here is where you provide context. First, what driving idea or problem is your research anchored in? Then, for added substance, cite existing research or insights from a subject matter expert, such as a thought leader in marketing, startup growth, or investment

2. Grounds for comparison Why have you chosen to examine the two things you’re analyzing instead of focusing on two entirely different things? What are you hoping to accomplish?

3. Thesis What argument or choice are you advocating for? What will be the before and after effects of going with either decision? What do you anticipate happening with and without this approach?

For example, “If we release an AI feature for our shopping cart, we will have an edge over the rest of the market before the holiday season.” The finished comparative analysis will weigh all the pros and cons of choosing to build the new expensive AI feature including variables like how “intelligent” it will be, what it “pushes” customers to use, how much it takes off the plates of customer service etc.

Ultimately, you will gauge whether building an AI feature is the right plan for your e-commerce shop.

4. Organize the scheme Typically, there are two ways to organize a comparative analysis report. First, you can discuss everything about comparison point “A” and then go into everything about aspect “B.” Or, you alternate back and forth between points “A” and “B,” sometimes referred to as point-by-point analysis.

Using the AI feature as an example again, you could cover all the pros and cons of building the AI feature, then discuss the benefits and drawbacks of building and maintaining the feature. Or you could compare and contrast each aspect of the AI feature, one at a time. For example, a side-by-side comparison of the AI feature to shopping without it, then proceeding to another point of differentiation.

5. Connect the dots Tie it all together in a way that either confirms or disproves your hypothesis.

For instance, “Building the AI bot would allow our customer service team to save 12% on returns in Q3 while offering optimizations and savings in future strategies. However, it would also increase the product development budget by 43% in both Q1 and Q2. Our budget for product development won’t increase again until series 3 of funding is reached, so despite its potential, we will hold off building the bot until funding is secured and more opportunities and benefits can be proved effective.”

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Lau F, Kuziemsky C, editors. Handbook of eHealth Evaluation: An Evidence-based Approach [Internet]. Victoria (BC): University of Victoria; 2017 Feb 27.

Handbook of eHealth Evaluation: An Evidence-based Approach [Internet].

Chapter 10 methods for comparative studies.

Francis Lau and Anne Holbrook .

10.1. Introduction

In eHealth evaluation, comparative studies aim to find out whether group differences in eHealth system adoption make a difference in important outcomes. These groups may differ in their composition, the type of system in use, and the setting where they work over a given time duration. The comparisons are to determine whether significant differences exist for some predefined measures between these groups, while controlling for as many of the conditions as possible such as the composition, system, setting and duration.

According to the typology by Friedman and Wyatt (2006) , comparative studies take on an objective view where events such as the use and effect of an eHealth system can be defined, measured and compared through a set of variables to prove or disprove a hypothesis. For comparative studies, the design options are experimental versus observational and prospective versus retro­­spective. The quality of eHealth comparative studies depends on such aspects of methodological design as the choice of variables, sample size, sources of bias, confounders, and adherence to quality and reporting guidelines.

In this chapter we focus on experimental studies as one type of comparative study and their methodological considerations that have been reported in the eHealth literature. Also included are three case examples to show how these studies are done.

10.2. Types of Comparative Studies

Experimental studies are one type of comparative study where a sample of participants is identified and assigned to different conditions for a given time duration, then compared for differences. An example is a hospital with two care units where one is assigned a cpoe system to process medication orders electronically while the other continues its usual practice without a cpoe . The participants in the unit assigned to the cpoe are called the intervention group and those assigned to usual practice are the control group. The comparison can be performance or outcome focused, such as the ratio of correct orders processed or the occurrence of adverse drug events in the two groups during the given time period. Experimental studies can take on a randomized or non-randomized design. These are described below.

10.2.1. Randomized Experiments

In a randomized design, the participants are randomly assigned to two or more groups using a known randomization technique such as a random number table. The design is prospective in nature since the groups are assigned concurrently, after which the intervention is applied then measured and compared. Three types of experimental designs seen in eHealth evaluation are described below ( Friedman & Wyatt, 2006 ; Zwarenstein & Treweek, 2009 ).

Randomized controlled trials ( rct s) – In rct s participants are randomly assigned to an intervention or a control group. The randomization can occur at the patient, provider or organization level, which is known as the unit of allocation. For instance, at the patient level one can randomly assign half of the patients to receive emr reminders while the other half do not. At the provider level, one can assign half of the providers to receive the reminders while the other half continues with their usual practice. At the organization level, such as a multisite hospital, one can randomly assign emr reminders to some of the sites but not others. Cluster randomized controlled trials ( crct s) – In crct s, clusters of participants are randomized rather than by individual participant since they are found in naturally occurring groups such as living in the same communities. For instance, clinics in one city may be randomized as a cluster to receive emr reminders while clinics in another city continue their usual practice. Pragmatic trials – Unlike rct s that seek to find out if an intervention such as a cpoe system works under ideal conditions, pragmatic trials are designed to find out if the intervention works under usual conditions. The goal is to make the design and findings relevant to and practical for decision-makers to apply in usual settings. As such, pragmatic trials have few criteria for selecting study participants, flexibility in implementing the intervention, usual practice as the comparator, the same compliance and follow-up intensity as usual practice, and outcomes that are relevant to decision-makers.

10.2.2. Non-randomized Experiments

Non-randomized design is used when it is neither feasible nor ethical to randomize participants into groups for comparison. It is sometimes referred to as a quasi-experimental design. The design can involve the use of prospective or retrospective data from the same or different participants as the control group. Three types of non-randomized designs are described below ( Harris et al., 2006 ).

Intervention group only with pretest and post-test design – This design involves only one group where a pretest or baseline measure is taken as the control period, the intervention is implemented, and a post-test measure is taken as the intervention period for comparison. For example, one can compare the rates of medication errors before and after the implementation of a cpoe system in a hospital. To increase study quality, one can add a second pretest period to decrease the probability that the pretest and post-test difference is due to chance, such as an unusually low medication error rate in the first pretest period. Other ways to increase study quality include adding an unrelated outcome such as patient case-mix that should not be affected, removing the intervention to see if the difference remains, and removing then re-implementing the intervention to see if the differences vary accordingly. Intervention and control groups with post-test design – This design involves two groups where the intervention is implemented in one group and compared with a second group without the intervention, based on a post-test measure from both groups. For example, one can implement a cpoe system in one care unit as the intervention group with a second unit as the control group and compare the post-test medication error rates in both units over six months. To increase study quality, one can add one or more pretest periods to both groups, or implement the intervention to the control group at a later time to measure for similar but delayed effects. Interrupted time series ( its ) design – In its design, multiple measures are taken from one group in equal time intervals, interrupted by the implementation of the intervention. The multiple pretest and post-test measures decrease the probability that the differences detected are due to chance or unrelated effects. An example is to take six consecutive monthly medication error rates as the pretest measures, implement the cpoe system, then take another six consecutive monthly medication error rates as the post-test measures for comparison in error rate differences over 12 months. To increase study quality, one may add a concurrent control group for comparison to be more convinced that the intervention produced the change.

10.3. Methodological Considerations

The quality of comparative studies is dependent on their internal and external validity. Internal validity refers to the extent to which conclusions can be drawn correctly from the study setting, participants, intervention, measures, analysis and interpretations. External validity refers to the extent to which the conclusions can be generalized to other settings. The major factors that influence validity are described below.

10.3.1. Choice of Variables

Variables are specific measurable features that can influence validity. In comparative studies, the choice of dependent and independent variables and whether they are categorical and/or continuous in values can affect the type of questions, study design and analysis to be considered. These are described below ( Friedman & Wyatt, 2006 ).

Dependent variables – This refers to outcomes of interest; they are also known as outcome variables. An example is the rate of medication errors as an outcome in determining whether cpoe can improve patient safety. Independent variables – This refers to variables that can explain the measured values of the dependent variables. For instance, the characteristics of the setting, participants and intervention can influence the effects of cpoe . Categorical variables – This refers to variables with measured values in discrete categories or levels. Examples are the type of providers (e.g., nurses, physicians and pharmacists), the presence or absence of a disease, and pain scale (e.g., 0 to 10 in increments of 1). Categorical variables are analyzed using non-parametric methods such as chi-square and odds ratio. Continuous variables – This refers to variables that can take on infinite values within an interval limited only by the desired precision. Examples are blood pressure, heart rate and body temperature. Continuous variables are analyzed using parametric methods such as t -test, analysis of variance or multiple regression.

10.3.2. Sample Size

Sample size is the number of participants to include in a study. It can refer to patients, providers or organizations depending on how the unit of allocation is defined. There are four parts to calculating sample size. They are described below ( Noordzij et al., 2010 ).

Significance level – This refers to the probability that a positive finding is due to chance alone. It is usually set at 0.05, which means having a less than 5% chance of drawing a false positive conclusion. Power – This refers to the ability to detect the true effect based on a sample from the population. It is usually set at 0.8, which means having at least an 80% chance of drawing a correct conclusion. Effect size – This refers to the minimal clinically relevant difference that can be detected between comparison groups. For continuous variables, the effect is a numerical value such as a 10-kilogram weight difference between two groups. For categorical variables, it is a percentage such as a 10% difference in medication error rates. Variability – This refers to the population variance of the outcome of interest, which is often unknown and is estimated by way of standard deviation ( sd ) from pilot or previous studies for continuous outcome.

Sample Size Equations for Comparing Two Groups with Continuous and Categorical Outcome Variables.

An example of sample size calculation for an rct to examine the effect of cds on improving systolic blood pressure of hypertensive patients is provided in the Appendix. Refer to the Biomath website from Columbia University (n.d.) for a simple Web-based sample size / power calculator.

10.3.3. Sources of Bias

There are five common sources of biases in comparative studies. They are selection, performance, detection, attrition and reporting biases ( Higgins & Green, 2011 ). These biases, and the ways to minimize them, are described below ( Vervloet et al., 2012 ).

Selection or allocation bias – This refers to differences between the composition of comparison groups in terms of the response to the intervention. An example is having sicker or older patients in the control group than those in the intervention group when evaluating the effect of emr reminders. To reduce selection bias, one can apply randomization and concealment when assigning participants to groups and ensure their compositions are comparable at baseline. Performance bias – This refers to differences between groups in the care they received, aside from the intervention being evaluated. An example is the different ways by which reminders are triggered and used within and across groups such as electronic, paper and phone reminders for patients and providers. To reduce performance bias, one may standardize the intervention and blind participants from knowing whether an intervention was received and which intervention was received. Detection or measurement bias – This refers to differences between groups in how outcomes are determined. An example is where outcome assessors pay more attention to outcomes of patients known to be in the intervention group. To reduce detection bias, one may blind assessors from participants when measuring outcomes and ensure the same timing for assessment across groups. Attrition bias – This refers to differences between groups in ways that participants are withdrawn from the study. An example is the low rate of participant response in the intervention group despite having received reminders for follow-up care. To reduce attrition bias, one needs to acknowledge the dropout rate and analyze data according to an intent-to-treat principle (i.e., include data from those who dropped out in the analysis). Reporting bias – This refers to differences between reported and unreported findings. Examples include biases in publication, time lag, citation, language and outcome reporting depending on the nature and direction of the results. To reduce reporting bias, one may make the study protocol available with all pre-specified outcomes and report all expected outcomes in published results.

10.3.4. Confounders

Confounders are factors other than the intervention of interest that can distort the effect because they are associated with both the intervention and the outcome. For instance, in a study to demonstrate whether the adoption of a medication order entry system led to lower medication costs, there can be a number of potential confounders that can affect the outcome. These may include severity of illness of the patients, provider knowledge and experience with the system, and hospital policy on prescribing medications ( Harris et al., 2006 ). Another example is the evaluation of the effect of an antibiotic reminder system on the rate of post-operative deep venous thromboses ( dvt s). The confounders can be general improvements in clinical practice during the study such as prescribing patterns and post-operative care that are not related to the reminders ( Friedman & Wyatt, 2006 ).

To control for confounding effects, one may consider the use of matching, stratification and modelling. Matching involves the selection of similar groups with respect to their composition and behaviours. Stratification involves the division of participants into subgroups by selected variables, such as comorbidity index to control for severity of illness. Modelling involves the use of statistical techniques such as multiple regression to adjust for the effects of specific variables such as age, sex and/or severity of illness ( Higgins & Green, 2011 ).

10.3.5. Guidelines on Quality and Reporting

There are guidelines on the quality and reporting of comparative studies. The grade (Grading of Recommendations Assessment, Development and Evaluation) guidelines provide explicit criteria for rating the quality of studies in randomized trials and observational studies ( Guyatt et al., 2011 ). The extended consort (Consolidated Standards of Reporting Trials) Statements for non-pharmacologic trials ( Boutron, Moher, Altman, Schulz, & Ravaud, 2008 ), pragmatic trials ( Zwarestein et al., 2008 ), and eHealth interventions ( Baker et al., 2010 ) provide reporting guidelines for randomized trials.

The grade guidelines offer a system of rating quality of evidence in systematic reviews and guidelines. In this approach, to support estimates of intervention effects rct s start as high-quality evidence and observational studies as low-quality evidence. For each outcome in a study, five factors may rate down the quality of evidence. The final quality of evidence for each outcome would fall into one of high, moderate, low, and very low quality. These factors are listed below (for more details on the rating system, refer to Guyatt et al., 2011 ).

Design limitations – For rct s they cover the lack of allocation concealment, lack of blinding, large loss to follow-up, trial stopped early or selective outcome reporting. Inconsistency of results – Variations in outcomes due to unexplained heterogeneity. An example is the unexpected variation of effects across subgroups of patients by severity of illness in the use of preventive care reminders. Indirectness of evidence – Reliance on indirect comparisons due to restrictions in study populations, intervention, comparator or outcomes. An example is the 30-day readmission rate as a surrogate outcome for quality of computer-supported emergency care in hospitals. Imprecision of results – Studies with small sample size and few events typically would have wide confidence intervals and are considered of low quality. Publication bias – The selective reporting of results at the individual study level is already covered under design limitations, but is included here for completeness as it is relevant when rating quality of evidence across studies in systematic reviews.

The original consort Statement has 22 checklist items for reporting rct s. For non-pharmacologic trials extensions have been made to 11 items. For pragmatic trials extensions have been made to eight items. These items are listed below. For further details, readers can refer to Boutron and colleagues (2008) and the consort website ( consort , n.d.).

Title and abstract – one item on the means of randomization used. Introduction – one item on background, rationale, and problem addressed by the intervention. Methods – 10 items on participants, interventions, objectives, outcomes, sample size, randomization (sequence generation, allocation concealment, implementation), blinding (masking), and statistical methods. Results – seven items on participant flow, recruitment, baseline data, numbers analyzed, outcomes and estimation, ancillary analyses, adverse events. Discussion – three items on interpretation, generalizability, overall evidence.

The consort Statement for eHealth interventions describes the relevance of the consort recommendations to the design and reporting of eHealth studies with an emphasis on Internet-based interventions for direct use by patients, such as online health information resources, decision aides and phr s. Of particular importance is the need to clearly define the intervention components, their role in the overall care process, target population, implementation process, primary and secondary outcomes, denominators for outcome analyses, and real world potential (for details refer to Baker et al., 2010 ).

10.4. Case Examples

10.4.1. pragmatic rct in vascular risk decision support.

Holbrook and colleagues (2011) conducted a pragmatic rct to examine the effects of a cds intervention on vascular care and outcomes for older adults. The study is summarized below.

Setting – Community-based primary care practices with emr s in one Canadian province. Participants – English-speaking patients 55 years of age or older with diagnosed vascular disease, no cognitive impairment and not living in a nursing home, who had a provider visit in the past 12 months. Intervention – A Web-based individualized vascular tracking and advice cds system for eight top vascular risk factors and two diabetic risk factors, for use by both providers and patients and their families. Providers and staff could update the patient’s profile at any time and the cds algorithm ran nightly to update recommendations and colour highlighting used in the tracker interface. Intervention patients had Web access to the tracker, a print version mailed to them prior to the visit, and telephone support on advice. Design – Pragmatic, one-year, two-arm, multicentre rct , with randomization upon patient consent by phone, using an allocation-concealed online program. Randomization was by patient with stratification by provider using a block size of six. Trained reviewers examined emr data and conducted patient telephone interviews to collect risk factors, vascular history, and vascular events. Providers completed questionnaires on the intervention at study end. Patients had final 12-month lab checks on urine albumin, low-density lipoprotein cholesterol, and A1c levels. Outcomes – Primary outcome was based on change in process composite score ( pcs ) computed as the sum of frequency-weighted process score for each of the eight main risk factors with a maximum score of 27. The process was considered met if a risk factor had been checked. pcs was measured at baseline and study end with the difference as the individual primary outcome scores. The main secondary outcome was a clinical composite score ( ccs ) based on the same eight risk factors compared in two ways: a comparison of the mean number of clinical variables on target and the percentage of patients with improvement between the two groups. Other secondary outcomes were actual vascular event rates, individual pcs and ccs components, ratings of usability, continuity of care, patient ability to manage vascular risk, and quality of life using the EuroQol five dimensions questionnaire ( eq-5D) . Analysis – 1,100 patients were needed to achieve 90% power in detecting a one-point pcs difference between groups with a standard deviation of five points, two-tailed t -test for mean difference at 5% significance level, and a withdrawal rate of 10%. The pcs , ccs and eq-5D scores were analyzed using a generalized estimating equation accounting for clustering within providers. Descriptive statistics and χ2 tests or exact tests were done with other outcomes. Findings – 1,102 patients and 49 providers enrolled in the study. The intervention group with 545 patients had significant pcs improvement with a difference of 4.70 ( p < .001) on a 27-point scale. The intervention group also had significantly higher odds of rating improvements in their continuity of care (4.178, p < .001) and ability to improve their vascular health (3.07, p < .001). There was no significant change in vascular events, clinical variables and quality of life. Overall the cds intervention led to reduced vascular risks but not to improved clinical outcomes in a one-year follow-up.

10.4.2. Non-randomized Experiment in Antibiotic Prescribing in Primary Care

Mainous, Lambourne, and Nietert (2013) conducted a prospective non-randomized trial to examine the impact of a cds system on antibiotic prescribing for acute respiratory infections ( ari s) in primary care. The study is summarized below.

Setting – A primary care research network in the United States whose members use a common emr and pool data quarterly for quality improvement and research studies. Participants – An intervention group with nine practices across nine states, and a control group with 61 practices. Intervention – Point-of-care cds tool as customizable progress note templates based on existing emr features. cds recommendations reflect Centre for Disease Control and Prevention ( cdc ) guidelines based on a patient’s predominant presenting symptoms and age. cds was used to assist in ari diagnosis, prompt antibiotic use, record diagnosis and treatment decisions, and access printable patient and provider education resources from the cdc . Design – The intervention group received a multi-method intervention to facilitate provider cds adoption that included quarterly audit and feedback, best practice dissemination meetings, academic detailing site visits, performance review and cds training. The control group did not receive information on the intervention, the cds or education. Baseline data collection was for three months with follow-up of 15 months after cds implementation. Outcomes – The outcomes were frequency of inappropriate prescribing during an ari episode, broad-spectrum antibiotic use and diagnostic shift. Inappropriate prescribing was computed by dividing the number of ari episodes with diagnoses in the inappropriate category that had an antibiotic prescription by the total number of ari episodes with diagnosis for which antibiotics are inappropriate. Broad-spectrum antibiotic use was computed by all ari episodes with a broad-spectrum antibiotic prescription by the total number of ari episodes with an antibiotic prescription. Antibiotic drift was computed in two ways: dividing the number of ari episodes with diagnoses where antibiotics are appropriate by the total number of ari episodes with an antibiotic prescription; and dividing the number of ari episodes where antibiotics were inappropriate by the total number of ari episodes. Process measure included frequency of cds template use and whether the outcome measures differed by cds usage. Analysis – Outcomes were measured quarterly for each practice, weighted by the number of ari episodes during the quarter to assign greater weight to practices with greater numbers of relevant episodes and to periods with greater numbers of relevant episodes. Weighted means and 95% ci s were computed separately for adult and pediatric (less than 18 years of age) patients for each time period for both groups. Baseline means in outcome measures were compared between the two groups using weighted independent-sample t -tests. Linear mixed models were used to compare changes over the 18-month period. The models included time, intervention status, and were adjusted for practice characteristics such as specialty, size, region and baseline ari s. Random practice effects were included to account for clustering of repeated measures on practices over time. P -values of less than 0.05 were considered significant. Findings – For adult patients, inappropriate prescribing in ari episodes declined more among the intervention group (-0.6%) than the control group (4.2%)( p = 0.03), and prescribing of broad-spectrum antibiotics declined by 16.6% in the intervention group versus an increase of 1.1% in the control group ( p < 0.0001). For pediatric patients, there was a similar decline of 19.7% in the intervention group versus an increase of 0.9% in the control group ( p < 0.0001). In summary, the cds had a modest effect in reducing inappropriate prescribing for adults, but had a substantial effect in reducing the prescribing of broad-spectrum antibiotics in adult and pediatric patients.

10.4.3. Interrupted Time Series on EHR Impact in Nursing Care

Dowding, Turley, and Garrido (2012) conducted a prospective its study to examine the impact of ehr implementation on nursing care processes and outcomes. The study is summarized below.

Setting – Kaiser Permanente ( kp ) as a large not-for-profit integrated healthcare organization in the United States. Participants – 29 kp hospitals in the northern and southern regions of California. Intervention – An integrated ehr system implemented at all hospitals with cpoe , nursing documentation and risk assessment tools. The nursing component for risk assessment documentation of pressure ulcers and falls was consistent across hospitals and developed by clinical nurses and informaticists by consensus. Design – its design with monthly data on pressure ulcers and quarterly data on fall rates and risk collected over seven years between 2003 and 2009. All data were collected at the unit level for each hospital. Outcomes – Process measures were the proportion of patients with a fall risk assessment done and the proportion with a hospital-acquired pressure ulcer ( hapu ) risk assessment done within 24 hours of admission. Outcome measures were fall and hapu rates as part of the unit-level nursing care process and nursing sensitive outcome data collected routinely for all California hospitals. Fall rate was defined as the number of unplanned descents to the floor per 1,000 patient days, and hapu rate was the percentage of patients with stages i-IV or unstageable ulcer on the day of data collection. Analysis – Fall and hapu risk data were synchronized using the month in which the ehr was implemented at each hospital as time zero and aggregated across hospitals for each time period. Multivariate regression analysis was used to examine the effect of time, region and ehr . Findings – The ehr was associated with significant increase in document rates for hapu risk (2.21; 95% CI 0.67 to 3.75) and non-significant increase for fall risk (0.36; -3.58 to 4.30). The ehr was associated with 13% decrease in hapu rates (-0.76; -1.37 to -0.16) but no change in fall rates (-0.091; -0.29 to 011). Hospital region was a significant predictor of variation for hapu (0.72; 0.30 to 1.14) and fall rates (0.57; 0.41 to 0.72). During the study period, hapu rates decreased significantly (-0.16; -0.20 to -0.13) but not fall rates (0.0052; -0.01 to 0.02). In summary, ehr implementation was associated with a reduction in the number of hapu s but not patient falls, and changes over time and hospital region also affected outcomes.

10.5. Summary

In this chapter we introduced randomized and non-randomized experimental designs as two types of comparative studies used in eHealth evaluation. Randomization is the highest quality design as it reduces bias, but it is not always feasible. The methodological issues addressed include choice of variables, sample size, sources of biases, confounders, and adherence to reporting guidelines. Three case examples were included to show how eHealth comparative studies are done.

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Appendix. Example of Sample Size Calculation

This is an example of sample size calculation for an rct that examines the effect of a cds system on reducing systolic blood pressure in hypertensive patients. The case is adapted from the example described in the publication by Noordzij et al. (2010) .

(a) Systolic blood pressure as a continuous outcome measured in mmHg

Based on similar studies in the literature with similar patients, the systolic blood pressure values from the comparison groups are expected to be normally distributed with a standard deviation of 20 mmHg. The evaluator wishes to detect a clinically relevant difference of 15 mmHg in systolic blood pressure as an outcome between the intervention group with cds and the control group without cds . Assuming a significance level or alpha of 0.05 for 2-tailed t -test and power of 0.80, the corresponding multipliers 1 are 1.96 and 0.842, respectively. Using the sample size equation for continuous outcome below we can calculate the sample size needed for the above study.

n = 2[(a+b)2σ2]/(μ1-μ2)2 where

n = sample size for each group

μ1 = population mean of systolic blood pressures in intervention group

μ2 = population mean of systolic blood pressures in control group

μ1- μ2 = desired difference in mean systolic blood pressures between groups

σ = population variance

a = multiplier for significance level (or alpha)

b = multiplier for power (or 1-beta)

Providing the values in the equation would give the sample size (n) of 28 samples per group as the result

n = 2[(1.96+0.842)2(202)]/152 or 28 samples per group

(b) Systolic blood pressure as a categorical outcome measured as below or above 140 mmHg (i.e., hypertension yes/no)

In this example a systolic blood pressure from a sample that is above 140 mmHg is considered an event of the patient with hypertension. Based on published literature the proportion of patients in the general population with hypertension is 30%. The evaluator wishes to detect a clinically relevant difference of 10% in systolic blood pressure as an outcome between the intervention group with cds and the control group without cds . This means the expected proportion of patients with hypertension is 20% (p1 = 0.2) in the intervention group and 30% (p2 = 0.3) in the control group. Assuming a significance level or alpha of 0.05 for 2-tailed t -test and power of 0.80 the corresponding multipliers are 1.96 and 0.842, respectively. Using the sample size equation for categorical outcome below, we can calculate the sample size needed for the above study.

n = [(a+b)2(p1q1+p2q2)]/χ2

p1 = proportion of patients with hypertension in intervention group

q1 = proportion of patients without hypertension in intervention group (or 1-p1)

p2 = proportion of patients with hypertension in control group

q2 = proportion of patients without hypertension in control group (or 1-p2)

χ = desired difference in proportion of hypertensive patients between two groups

Providing the values in the equation would give the sample size (n) of 291 samples per group as the result

n = [(1.96+0.842)2((0.2)(0.8)+(0.3)(0.7))]/(0.1)2 or 291 samples per group

From Table 3 on p. 1392 of Noordzij et al. (2010).

This publication is licensed under a Creative Commons License, Attribution-Noncommercial 4.0 International License (CC BY-NC 4.0): see https://creativecommons.org/licenses/by-nc/4.0/

• Cite this Page Lau F, Holbrook A. Chapter 10 Methods for Comparative Studies. In: Lau F, Kuziemsky C, editors. Handbook of eHealth Evaluation: An Evidence-based Approach [Internet]. Victoria (BC): University of Victoria; 2017 Feb 27.
• PDF version of this title (4.5M)

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• Introduction
• Types of Comparative Studies
• Methodological Considerations
• Case Examples
• Example of Sample Size Calculation

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The Rising of the Avant-Garde Movement In the 1980s People’s Republic of China: A Cultural Practice of the New Enlightenment , Jingsheng Zhang

Theses/Dissertations from 2020 2020

L’ Entre- Monde : The Cinema of Alain Gomis , Guillaume Coly

Digesting Gender: Gendered Foodways in Modern Chinese Literature, 1890s–1940s , Zhuo Feng

The Deconstruction of Patriarchal War Narratives in Svetlana Alexievich’s The Unwomanly Face of War , Liubov Kartashova

Pushing the Limits of Black Atlantic and Hispanic Transatlantic Studies Through the Exploration of Three U.S. Afro-Latio Memoirs , Julia Luján

Taiwanese Postcolonial Identities and Environmentalism in Wu Ming-Yi’s the Stolen Bicycle , Chihchi Sunny Tsai

Games and Play of Dream of the Red Chamber , Jiayao Wang

Theses/Dissertations from 2019 2019

Convertirse en Inmortal, 成仙 ChéngxiāN, Becoming Xian: Memory and Subjectivity in Cristina Rivera Garza’s Verde Shanghai , Katherine Paulette Elizabeth Crouch

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Emerging Populations: An Analysis of Twenty-First Century Caribbean Short Stories , Jeremy Patterson

Time, Space and Nonexistence in Joseph Brodsky's Poetry , Daria Smirnova

Theses/Dissertations from 2018 2018

Through the Spaceship’s Window: A Bio-political Reading of 20th Century Latin American and Anglo-Saxon Science Fiction , Juan David Cruz

The Representations of Gender and Sexuality in Contemporary Arab Women’s Literature: Elements of Subversion and Resignification. , Rima Sadek

Insects As Metaphors For Post-Civil War Reconstruction Of The Civic Body In Augustan Age Rome , Olivia Semler

Theses/Dissertations from 2017 2017

Flannery O’Connor’s Art And The French Renouveau Catholique: A Comparative Exploration Of Contextual Resources For The Author’s Theological Aesthetics Of Sin and Grace , Stephen Allen Baarendse

The Quixotic Picaresque: Tricksters, Modernity, and Otherness in the Transatlantic Novel, or the Intertextual Rhizome of Lazarillo, Don Quijote, Huck Finn, and The Reivers , David Elijah Sinsabaugh Beek

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Narrating Pain and Freedom: Place and Identity in Modern Syrian Poetry (1970s-1990s) , Manar Shabouk

Theses/Dissertations from 2016 2016

The Development of ‘Meaning’ in Literary Theory: A Comparative Critical Study , Mahmoud Mohamed Ali Ahmad Elkordy

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Theses/Dissertations from 2015 2015

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Female Representations in Contemporary Postmodern War Novels of Spain and the United States: Women as Tools of Modern Catharsis in the Works of Javier Cercas and Tim O'Brien , Joseph P. Weil

Theses/Dissertations from 2014 2014

Poetic Appropriations in Vergil’s Aeneid: A Study in Three Themes Comprising Aeneas’ Character Development , Edgar Gordyn

Ekphrasis and Skepticism in Three Works of Shakespeare , Robert P. Irons

Theses/Dissertations from 2013 2013

The Role of the Trickster Figure and Four Afro-Caribbean Meta-Tropes In the Realization of Agency by Three Slave Protagonists , David Sebastian Cross

Putting Place Back Into Displacement: Reevaluating Diaspora In the Contemporary Literature of Migration , Christiane Brigitte Steckenbiller

Using Singular Value Decomposition in Classics: Seeking Correlations in Horace, Juvenal and Persius against the Fragments of Lucilius , Thomas Whidden

Theses/Dissertations from 2012 2012

Decolonizing Transnational Subaltern Women: The Case of Kurasoleñas and New York Dominicanas , Florencia Cornet

Representation of Women In 19Th Century Popular Art and Literature: Forget Me Not and La Revista Moderna , Juan David Cruz

53x+m³=Ø? (Sex+Me=No Result?): Tropes of Asexuality in Literature and Film , Jana -. Fedtke

Argentina in The African Diaspora: Afro-Argentine And African American Cultural Production, Race, And Nation Building in the 19th Century , Julia Lujan

Male Subjectivity and Twenty-First Century German Cinema: Gender, National Idenity, and the Problem of Normalization , Richard Sell

Theses/Dissertations from 2011 2011

Blue Poets: Brilliant Poetry , Evangelin Grace Chapman-Wall

Sickness of the Spirit: A Comparative Study of Lu Xun and James Joyce , Liang Meng

Dryden and the Solution to Domination: Bonds of Love In the Conquest of Granada , Lydia FitzSimons Robins

Theses/Dissertations from 2010 2010

The Family As the New Collectivity of Belonging In the Fiction of Bharati Mukherjee and Jhumpa Lahiri , Sarbani Bose

Lyric Transcendence: the Sacred and the Real In Classical and Early-Modern Lyric. , Larry Grant Hamby

Abd al-Rahman Al-Kawakibi's Tabai` al-Istibdad wa Masari` al-Isti`bad (The Characteristics of Despotism and The Demises of Enslavement): A Translation and Introduction , Mohamad Subhi Hindi

Re-Visions: Nazi Germany and Fascist Italy In German and Italian Film and Literature , Kristina Stefanic Brown

Plato In Modern China: A Study of Contemporary Chinese Platonists , Leihua Weng

Making Victims: History, Memory, and Literature In Japan's Post-War Social Imaginary , Kimberly Wickham

Theses/Dissertations from 2009 2009

The Mirrored Body: Doubling and Replacement of the Feminine and androgynous Body In Hadia Said'S Artist and Haruki Murakami'S Sputnik Sweetheart , Fatmah Alsalamean

Making Monsters: The Monstrous-Feminine In Horace and Catullus , Casey Catherine Moore

Not Quite American, Not Quite European: Performing "Other" Claims to Exceptionality In Francoist Spain and the Jim Crow South , Brittany Powell

Developing Latin American Feminist Theory: Strategies of Resistance In the Novels of Luisa Valenzuela and Sandra Cisneros , Jennifer Lyn Slobodian

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• Published: 27 September 2024

A comparative study of hormonal contraceptive use and vitamin D levels at Gondar Town 2023

• Elias Chane 1 ,
• Bisrat Birke Teketlew 2 ,
• Dereje Mengesha Berta 2 ,
• Abiy Ayele Angelo 3 ,
• Negesse Cherie 4 ,
• Mebratu Tamir 5 ,
• Zufan Yiheyis Abriham 5 &
• Amare Mekuanint 1  

Scientific Reports volume  14 , Article number:  22162 ( 2024 ) Cite this article

Metrics details

• Biochemistry
• Endocrinology
• Medical research

Vitamin D deficiency is an emerging public health problem globally, with devastating health consequences. Some studies suggest that exogenous sex hormones, found in hormonal contraceptives, may enhance vitamin D levels. However, the reasons for this association are not fully understood, as women using hormonal contraception may have different lifestyle habits affecting their vitamin D status. Therefore, this study seeks to explore the relationship between hormonal contraceptive use and vitamin D levels. A Facility based comparative cross-sectional study was conducted in Gondar town from February to April 2023, involving a total of 162 women using three types of hormonal contraceptives (Norplant, DMPA, and COC) and 162 age and BMI-matched non-users as controls in a 1:1 ratio. Participants were selected using systematic random sampling. A semi-structured questionnaire was used to collected data regarding the socio-demographic, economic, obstetric, lifestyle, and clinical information. 5 milliliters of blood samples were collected from each participant for Laboratory analysis of serum vitamin D, calcium, and alkaline phosphates using a Beckman Coulter chemistry analyzer. Independent t-tests, ANOVA with post hoc Bonferroni test was used to compare statistics between the two groups, and logistic regression models to identify factors associated with Vitamin D deficiency. The mean serum Vitamin D levels of Norplant, DMPA, and COC users were 24.08 (± 5.17), 24.83 (± 5.52), and 31.90 (± 6.94) respectively; whereas control group has mean Vitamin D level of 22.00 (± 7.97). On the current study the prevalence of Vitamin D deficiency (< 20 ng/ml) among hormonal contraceptive users was found to be 21.6% (35/162), whereas 48.14% (78/162) of non-user controls had vitamin D deficiency. The odds of having Vitamin D deficiency was higher among participants who attained higher education, who never eat fish and have never been used vitamin D Supplements. However, the use of combined oral contraceptives (COC) shown to reduce the odd of having vitamin D deficiency by 90%. Similarly, individuals with normal and hypercalcemia state shown to have lower odd of having Vitamin D deficiency. Users of combined oral contraceptives (COC) had significantly higher mean serum Vitamin D levels compared to users of Norplant and DMPA, as well as non-users. The prevalence of Vitamin D deficiency was lower among COC users compared to non-users, highlighting a potential protective effect of COC use against Vitamin D deficiency.

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Introduction.

Vitamin D (calciferol) is a fat-soluble vitamin that is important for normal functions of the body 1 , 2 . It is present in the body in to forms Vitamin D3 (Cholecalciferol) and Vitamin D2 (Ergocalciferol). Cholecalciferol secreted in the skin in response to active sunlight exposure whereas Ergocalciferol usually obtained from diet 1 . Vitamin D regulate calcium and phosphorus level by regulating their metabolism and absorption 3 . In addition, Vitamin D also demonstrated to plays a role in immune cells function, cell growth, and inflammatory responses 4 , 5 .

Even though vitamin D is crucial for normal function of the body, several epidemiological studies have shown that a significant percentage of the population globally have insufficient levels of this important nutrient 1 , 6 , 7 . This is very concerning since vitamin D deficiency and insufficiency have been linked to a higher risk of several health issues, including osteoporosis, adverse cardiovascular outcomes, autoimmune disease, and cancers 7 , 8 , 9 . Some reports have also indicated that vitamin D plays a role in various forms of adverse reproductive outcomes on the offspring 10 . Blood 25-hydroxycholecalciferol (25(OH) D) level believed to be the best indicator of person vitamin D status is, as it reflects both cutaneous synthesis and dietary consumption of the nutrient 7 .

Vitamin D deficiency is currently a public health problem, affecting individuals of all classes and populations with varying epidemiology 1 , 11 . The prevalence of vitamin D deficiency varies across different regions, with prevalence of serum 25(OH)D deficiency (< 30 nmol/L) varied from 5.5% in the Region of the Americas to 35.2% in the Eastern Mediterranean Region. It is also reported that females were more vulnerable to vitamin D deficiency than males 11 . It has been gaining much attention globally due to its health effects on the reduction of mortality and morbidity 1 , 11 .

Several human factors reported to affect vitamin D levels in the body. The most significant factor is sun light exposure, since skin produces vitamin D when exposed to sun. Moreover, individuals age, skin color, Body mass index (BMI) and dietary intake of vitamin D-rich food can also influence vitamin D levels 1 , 12 . It is also believed that Hormonal contraceptives (HCs) containing estrogens or estrogens coupled with progestins may affect vitamin D serum concentrations 13 . Some studies suggest exogenous estrogen may improve vitamin D status, but the etiology is unclear because women who use hormones may make lifestyle choices that differentially affect vitamin D status 10 , 13 .

Hormonal Contraceptives (HCs) are birth control methods containing artificial Estrogen (Ethinylestradiol (EE)) and/or progestin 14 . These contraceptives work by shifting hormone levels in body 14 , 15 . Ethinylestradiol (EE2) is a analogous of 17β-estradiol 16 , the major endogenous human estrogen. EE2 is used in many forms of hormonal contraception and is one of the most commonly used medications for this purpose. EE2 exert its function by acting as a ling and activating the estrogen receptor and exerts its hormonal effect 16 , 17 . Another component of HC which administrated solely or in combination with EE is progestin 18 , 19 , 20 , 21 . The molecularly modified progestin has strong progestogenic effects. Molecular modifications, such as the adding of a 17α-alkyl group and alteration to the steroid backbone, enhance the efficiency of progestins in HC preparations 19 .

Epidemiological studies reported that HCs are the most commonly used methods of birth control worldwide 22 , 23 . World Fertility and Family Planning 2020 reported that in 2019, 49% of all women of reproductive age were using contraceptives globally 24 and half of them were using HCs containing progestin and/or Estrogen 25 . The hormonal contraceptive prevalence varies globally, with higher rates observed in developed countries compared to developing nations 23 . In Ethiopia, the contraceptive prevalence rate (CPR) is currently 22.2% 12 .

Serum level of alkaline phosphate (ALP) frequently analyzed along with Vitamin D, which is a crucial indicator of bone health 26 , 27 , 28 . ALP is an enzyme present in liver, bones, kidneys, and digestive system; and that is involved in the process of bone mineralization, and elevated levels of ALP may indicate bone turnover 13 . Calcium is another essential nutrient frequently analyzed along with ALP and Vitamin D; that plays a role in bone growth and regeneration, muscle function, and nerve transmission 26 , 29 .

Hormonal contraceptives are generally utilized by women for birth control and family planning purpose. However, there are some evidences suggesting they may affect some biomolecules, including their vitamin D status 10 , 30 , 31 . Few studies have investigated the relationship between HC and serum vitamin D levels, with conflicting results 32 , 33 , 34 , 35 . Some studies reported combined HC shown to increase blood levels of vitamin D, although the exact molecular mechanism is unclear 10 , 13 , 34 , 35 , 36 . There is also report affirming the use of combined oral contraceptives (COC) may decrease Vitamin D levels 37 . On the other hand, other epidemiological studies investigating the association between hormonal contraceptive usage and serum vitamin D levels have reported contradictory findings. Some studies have found no significant association between hormonal contraceptive use and serum vitamin D levels or even lower vitamin D level among hormonal contraceptive users 37 , 38 .

Additional investigation about the association between HC and vitamin D is needed to briefly explain their association, because of the potential effects of HC preparations on blood vitamin D levels. Moreover, Understanding the variables that influence vitamin D levels among those on HC may help healthcare professionals to identify those who are at risk of vitamin D deficiency and develop targeted medicines to address this issue. The purpose of this study is to analyze blood vitamin D levels and identify the prevalence of Vitamin D deficiency and associated factors among hormonal contraceptive users and non-user controls in Gondar town in 2023, with a focus on serum ALP and calcium levels.

Method and material

Study area, design, and period.

After receiving ethical clearance letter from “School of Biomedical and Laboratory Sciences Institutional Review Board by reference number SBLS/184/14; A facility-based comparative cross-sectional study was conducted. The study was carried out at three healthcare institutions in Gondar town (The University of Gondar Comprehensive Specialized Hospital, Ethiopian Family Guidance Association Gondar branch, and Gondar Poly Clinic). The study data was collected from February 6 to April 28, 2023.

Source population

All eligible reproductive age group women who visited the two institutes for family planning service in 2023 (hormonal contraceptives user group). And a control group of age and BMI matched women who were refrain from using hormonal contraceptives.

Study population

The study populations were HC user who visited the selected health institutes seeking routine family planning services and consultations, with selection based on meeting the defined inclusion criteria at the time of data collection from February 6 to April 28 2023, while the second cohort comprised age and BMI-matched women who were not using hormonal contraceptives.

Eligibility criteria

Inclusion criteria for hormonal contraceptives user group.

Volunteer women aged 18–45 years with regular use of hormonal contraceptives (Norplant, DMPA and COC) for at least 6 months. And able to provide information related to demography, life and clinical variables; and willing to provide 5 ml of blood.

Inclusion criteria for non-user controls

Volunteer women aged 18–45 years with abstinence of hormonal contraceptives usage in the past 6 months. And able to provide information related to demography, life and clinical variables; and willing to provide 5 ml of blood.

Exclusion criteria for both groups

Women with poor HC compliance, mental and hearing problem or other health issues limiting their ability to provide information. women on anti-Tuberculosis and antiepileptic medications. Women with acute or chronic liver disease. Women with acute or chronic kidney disease. Pregnant or lactating women or history of pregnancy or miscarriage in the past 12 months History of vitamin D deficiency or calcium metabolism disorders.

Dependent variable

Serum vitamin D level.

Independent variables

Socio-demographic factors (Age, Educational Status, Monthly Income, Marital Status, Residency, Housing Condition and Occupation).

Anthropometric (BMI, WHR and Skin color).

Clinical and obstetric conditions (Blood pressure, hormonal contraceptive class, duration of hormonal contraceptive usage, gravidity, and parity).

Behavioral characteristics (Coffee drinking habit, physical activity, smoking and alcohol consumption).

Sun light exposure modulators (Sunlight exposure time in a day, utilization of sun screen lotions, type of clothing).

Usual food content and Dietary diversity.

Sample size and sampling technique

A total of 324 Women (162 for HC user group and 162 for Non-user Controls) was enrolled on the study. Systematic random sampling technique was applied to recruit participants. The sample size was allocated proportionally. We obtained data from the three health institutes in the previous year (2022) to determine the skip interval for our systematic random sample during the duration of data collection. Every 5th of study participants arriving to the clinics were asked for participation and included in the study.

Operational definition

Hormonal contraceptive user  women aged 18 years and older who have consistently used hormonal contraceptives (such as combined oral contraceptives (COC), Depo-medroxyprogesterone acetate (DMPA), or Norplant) for a minimum duration of 6 months 39 .

Hormonal contraceptive non-user (Controls)  Women of reproductive age group abstains of HC use, individuals who use non-hormonal contraceptives (Condoms, Cervical Cap and diaphragm).

Vitamin D deficiency Serum levels of 25-hydroxyvitamin D (25(OH)D) below < 20 ng/mL or < 50 nmol/L 13 , 40 .

Vitamin D insufficiency serum levels of 25-hydroxyvitamin D (25(OH)D) between 20 and 30 ng/mL or 50–75 nmol/L 13 , 40 .

Skin Color - Skin color classification is based on the Fitzpatrick scale to describe skin pigmentation as (“Type IV” light brown, “Type V” dark brown Type and “VI- very dark brown”).

Physical exercise or activity  refers to any physiological movement produced by skeletal muscles that needs energy expenditure and raises heart rate at least once every day for 20–30 min in a continuous manner. Walking, running, cycling, swimming, weight lifting, and participating in other sports or fitness classes are all examples of this. For the objectives of this study, physical exercise or activity will be measured in terms of frequency (number of sessions per week) and length (minutes per session). “Active” individuals engage in regular physical exercise or activity for at least 150 min per week, while “inactive” individuals report no engagement in physical exercise or activity for at least 150 min per week 41 .

Sun light exposure time in a day : Common sunlight exposure time in a day refers to the duration of time spent outdoors in direct sunlight, which can contribute to the synthesis of vitamin D in the skin. For the purpose of this study, sunlight exposure time will be categorized into three time periods: “Sun raise/morning” The time period between 7:00 and 9:00 AM, “Mid-day” The time period between 10:00 and 3:00 PM, and Sunset/evening “The time period between 4:00 and 6:00 PM”.

Utilization of Sunscreen Lotion  refers to the frequency of applying sunscreen on the skin to protect it from the harmful effects of UV radiation from the sun. For the purpose of this study among study participants, sunscreen usage will be categorized into three levels “ Sunscreen users” Participants who regularly use sunscreen or lotion when exposed to sunlight, regardless of their eating habits. “ Sunscreen non-users ” Participants who do not use sunscreen or lotion when exposed to sunlight, regardless of their eating habits. “ Variable sunscreen or lotion users ” Participants who inconsistently use sunscreen or lotion when exposed to sunlight, depending on factors such as the weather or activities they are engaged in.

Utilization of Umbrella  refers to the frequency of using Umbrella to protect skin from the harmful effects of UV radiation from the sun. For the purpose of this study umbrella use will be categorized in to three usage level “ Regular Umbrella Users ” Participants who use an umbrella for sun protection daily, or on a consistent basis when outdoors. “ Occasional Umbrella Users ” Participants who use an umbrella for sun protection on a weekly or monthly basis, depending on weather conditions or activities. “ Umbrella Non-Users ” Participants who never use an umbrella for sun protection, regardless of weather or outdoor activities.

Dietary Diversity refers to the variety of different foods and food groups consumed by an individual within a specified period, typically a day or a week. For the purpose of this study dietary diversity will be categorized “ High Dietary Diversity ” typically consume foods from fruits, vegetables, grains, proteins, dairy, and fats/oils. “ Moderate Dietary Diversity ” individual consumes foods from a variety of food groups but may not include all major food groups or may lack variety within specific food groups. “Low Dietary Diversity” Low dietary diversity signifies limited variation in food choices, with a focus on a narrow range of foods or heavy reliance on a few food groups. “ Very low diet diversity ” consume the same types of foods or neglect certain food groups.

Dietary Vitamin D intake quantification  To be considered a consumer of Vitamin D through dietary intake, participants must meet the following criteria: “ Liver Consumer ”: Having consumed a serving of beef liver greater than 150 g in one meal per day. “ Fish Consumer ”: Having a meal consisting of medium 85–170 g of fatty fish, such as salmon and sardines, per day “ Fish Oil Consumer ”: Having consumed fish oil products containing 0.25–0.5 g (1–2 teaspoons) of combined EPA (eicosapentaenoic acid) and DHA (docosahexaenoic acid) per day. “ Fortified Cereals Consumer ”: Having consumed at least 250 g of fortified cereal products per day. “ Egg Consumer ”: Having a meal consisting of at least 3 eggs per day. “ Fortified Dairy Products Consumer ”: Having consumed serving sizes of fortified dairy products that provide about 100 IU of Vitamin D, such as: 1 cup of fortified milk (about 250 ml) or 1 cup of fortified yogurt (about 250 ml) or 1.5 ounces of fortified cheese.

Serum calcium level  “Hypocalcemia” serum calcium < 8.5 mg/dL, “Hypercalcemia” serum calcium > 10.5 mg/dL.

Data collection tool and procedure

Individuals who met the inclusion criteria for each study group were invited to participate after being fully briefed about the study’s objectives. Participants who agreed to participate were asked to give written signed informed consent. A standard questionnaire was prepared and pre-tested to collected variables about sociodemographic, economical, behavioral and clinical characteristics. The questionnaire was first prepared in English, and then it was translated into local Amharic language. the prepared questions were pre-tested at “ Azezzo ” health center to adapt to the local context based on the study objectives through face-to-face interview. Information on hormonal contraceptive use, including type, dosage, and duration, was also obtained from medical records.

Weight in kilograms (kg) was measured to the closest tenth kg with a digital balance attached to a Seca digital weighted scale (Germany), with subjects barefoot and dressed in light clothing. Height (cm) was measured twice and reported to the nearest centimeter using a Seca (Germany) calibrated Stadiometer. BMI (kg/m 2 ) was calculated using measured height and weight. The waist circumference was measured with a meter halfway between the lowest rib border and the iliac crest. The hip circumference was measured with a meter over the widest region of the hips, crossing behind the back. Blood pressure (BP) was measured using an analog sphygmomanometer (Omron blood pressure monitor Japan) and stethoscope (Omron Japan).

Following the interview, the upper arm region was thoroughly cleansed with alcohol wipes, and subsequently allowed to completely dry. The needle was then swiftly inserted at a 30–45-degree angle to obtain venous blood sample of 5 ml from the medial cubital vein of the left arm using a syringe, which was then transferred into a gel-coated serum separator tube (SST) with a specific ID label. The blood sample was left to coagulate at room temperature for half an hour before being centrifuged at 5000 rotations per minute (RPM) for 3 min. The resulting serum was then moved to a sterile “Nunc tube” and transported to the university of Gondar comprehensive specialized hospital clinical chemistry section for analysis.

Serum vitamin D levels were analyzed utilizing a standardized laboratory immunoassay technique on the Unicel DxI 800 Beckman Coulter Clinical Chemistry Analyzer, with Beckman Coulter reagents. The Vitamin D Total assay employed a two-step competitive binding immunoenzymatic procedure, wherein the initial incubation involves the addition of a sample to a reaction vessel with a DBP releasing agent and paramagnetic particles coated with sheep monoclonal anti-25(OH) vitamin D antibody. This process allows for the release of 25(OH) vitamin D from DBP and binding to the immobilized monoclonal anti-25(OH) vitamin D on the solid phase. Subsequently, a 25(OH) vitamin D analogue-alkaline phosphatase conjugate is introduced to compete for binding to the immobilized monoclonal anti-25(OH) vitamin D. Following a subsequent incubation, materials bound to the solid phase are separated in a magnetic field while unbound materials are washed away. The chemiluminescent substrate is then added to the vessel, and the light generated by the reaction is measured using a luminometer. The intensity of light production is inversely related to the concentration of 25(OH) vitamin D in the sample. The result was reported as ng/ml.

Serum Calcium and ALP analyses were conducted using the Beckman Coulter DxC700 Automated Chemistry Analyzer, with test results reported in mg/dl for calcium and International Units per liter (IU/L) for enzymatic ALP levels. The DxC 700 AU clinical chemistry analyzer represents the latest technological advancement produced by Beckman Coulter Inc., a company under the Danaher Corporation based in Brea, California, United States.

Data analysis and interpretation

The data collected underwent manual verification, categorization, and coding procedures. It was then entered into EPI-DATA software for organization. Subsequently, The data underwent rigorous cleaning procedures, including dealing with missing values, correcting inaccuracies, removing duplicates and handling missing values, ensuring data consistency and transferred to STATA VERSION 17 for detailed descriptive statistical analysis. The normal distribution of continuous variables was scrutinized utilizing the Kolmogorov-Smirnov test. Various statistical methods such as Independent t-test, ANOVA, and logistic regression were employed to assess and compare values across different groups, while also identifying factors associated with Vitamin D deficiency.

A one-way ANOVA with Bonferroni post-hoc test was executed to compare the mean serum levels of Vitamin D, Total Calcium, and Alkaline phosphate between Hormonal contraceptive users and the control group. Furthermore, binary and multivariate logistic regression models were utilized to ascertain the factors linked to Vitamin D deficiency. Variables demonstrating a significance level of ≤ 0.25 in the bivariate analysis were reevaluated in the multivariate logistic regression model to control for potential confounding variables and to pinpoint the independent factors related to Vitamin D deficiency. Both crude and adjusted odds ratios (COR and AOR) were computed, along with their corresponding 95% confidence intervals (CI), to determine the strength of associations between variables. A statistical significance of < 0.05 was assumed for the multivariate regression model to assess statistical significance.

Ethical considerations

The study protocol was approved by the Institutional Review Board of School of Biomedical and Laboratory Sciences, college of medicine and health sciences University of Gondar; by reference number SBLS/184/14. The study was conducted in accordance with the Declaration of Helsinki guidelines and regulations. Permission was also gained from the medical director of each three of the health institute the data was collected. “Informed consent” was obtained from all participants (Supplementary material 1 ), and confidentiality of data was maintained throughout the study. In addition, to ensure confidentiality, codes were used as identifier of participants on the questionnaire and laboratory requests. The collected data was not used for another purpose other than the present study.

Socio-demographic characteristics

In the current study a total of 324 women were included in two study groups. There were 162 women who were using hormone-based contraceptives (Norplant, DMPA, and COC) in one group, while the other group consisted of 162 women who did not use hormonal contraceptives, matched by age and BMI. The mean age for women using hormonal contraceptives was 26.88 years (± 5.50), and for the control group, it was 26.80 years (± 5.60). Over half of the study participants, 178 (54.92%) had attained at least a secondary education level or higher (Table  1 ).

Anthropometric, clinical and obstetric characteristics

The mean body mass index (BMI) for those using hormonal contraceptives was 22.76 (± 3.85), and 22.52 (± 3.85) for the non-user control group. Out of the participants, 155 (47.84%) had dark brown (type V) skin, while only 74 (22.84%) had light skin (type IV). Additionally, 154 (47.53%) of the study subjects were in a primigravida state, with only 27 (8.33%) being nulliparous (Table  2 ).

Hormonal contraceptive status of participants

The current study enrolls users of three contraceptive 54 in each group and age and BMI matched non-user controls (Fig.  1 ).

Hormonal contraceptive status of study participants in Gondar town, Northwest Ethiopia, 2023 ( N  = 324, Gondar, 2023).

Dietary intake of vitamin D rich foods

About 183 (56.48%) of the women participated on this study never consumed fish and 312 (96.29%) never consumed Fish oil. 283 (87.34%) of participants reported on never been used vitamin D supplements ever. On the other hand, 100 (30.86%) consumed fortified milk routinely (Table  3 ).

Sunlight exposure and lifestyle characteristics

About 93 (28.70%) of participants reported on that they never use Sun screen lotion and 194 (59.88%) of the participants usually use umbrella whenever they go outside of home. 126 (38.89%) of the participants usually exposed to sun light on the mid-day. 220 (67.90%) of the participants reported vegetables as their usual food content (Table  4 ).

Serum vitamin D, calcium and alkaline phosphate level of participants

The mean serum Vitamin D levels were found to be 26.94 (± 6.87) for hormonal contraceptive users and 22.00 (± 7.97) for control group participants (Table  5 ). It was observed that different types of hormonal contraceptives had varying effects on the serum Vitamin D levels of the study participants, as indicated in the ANOVA table below. Specifically, the mean Vitamin D levels for Norplant, DMPA, and COC were 24.08 (± 5.17), 24.83 (± 5.52), and 31.90 (± 6.94) respectively (Table  6 ). Furthermore, the Bonferroni post hoc analysis revealed that the mean serum Vitamin D levels differed significantly between each contraceptive class and were found to be statistically significant ( p  < 0.001) (Table  6 ).

Prevalence of vitamin D deficiency and insufficiency

On the current study the prevalence of Vitamin D deficiency (< 20 ng/ml) among hormonal contraceptive users was found to be 21.6% (35/162), whereas 48.14% (78/162) of non-user controls had vitamin D deficiency. On the other hand, the prevalence of Vitamin D insufficiency (20.01–29.99 ng/ml) was found to be 68.51% (111/162) among hormonal contraceptive users and 83.33% (135/162) among non-user controls. The overall prevalence of Vitamin D deficiency and insufficiency among the study participants found to be 113 (34.87%) and 246 (75.92%) respectively (Table  7 ).

Factors associated with vitamin D deficiency among participants

Variable screening was carried out to choose independent variables for the regression model. The independence and exclusiveness of each predictor variable were confirmed during the design phase, while variables exhibiting multicollinearity were excluded from the regression model in the second analysis stage. A chi-squared (chi2) test was conducted for each categorical independent variable. Variables that met the assumption were then analyzed in a bivariate logistic regression. The Hosmer–Lemeshow goodness of fit test was performed for the logistic regression model, yielding a p -value of 0.70.

In the bivariable analysis, the following predictors were found to have a significant association ( p  < 0.05) with Vitamin D deficiency: hormonal contraceptive status, type of hormonal contraceptive, educational status, systolic blood pressure (SBP), food diversity score, use of sunscreen lotion, use of an umbrella, habit of consuming fish, and serum calcium level. All variables with a p -value < 0.25 in binary regression were included in the multivariable logistic analysis. In the multivariable analysis, it was observed that participants with higher education ( p  = 0.011), those who never consume fish ( p  = 0.018), and individuals who do not use Vitamin D supplements ( p  = 0.016) had higher odds of experiencing vitamin D deficiency. On the other hand, users of combined oral contraceptives (COC) ( p  = 0.000) and those with normal or high levels of calcium in the blood had lower odds of developing vitamin D deficiency, with p -values of (0.041) and (0.049) respectively (Table  8 ).

The odds of having Vitamin D deficiency was 2.99 times higher among participants who attained higher education. Conversely, Participant who never eat fish shown to have increased odds of having Vitamin D deficiency by 12.36 times. Participants who reported to have never been used vitamin D Supplements was observed to have 4.1 times higher odds of having Vitamin D deficiency. However, user of combined oral contraceptives (COC) revealed to be 90% less likely to for occurrence of Vitamin D deficiency with AOR of 0.10. Similarly, individuals with normal serum calcium level or hypercalcemia state shown to have lower odd of having Vitamin D deficiency (Table  8 ).

In the present study the users of Hormonal contraceptives (Norplant, DMPA and COC) had higher mean value of serum Vitamin D (25(OH)D) level than controls. These findings were consistent with previous findings from Italy 42 , Norway 43 , Germany 34 , United Kingdom 32 , 44 , Netherlands 45 , United State 10 , 33 , 36 , 46 , 47 , Canada 31 , 48 and Uruguay 49 . The observed higher mean serum vitamin D levels among hormonal contraceptive users compared to non-users could potentially be explained by the role of hormonal contraceptives in increasing vitamin D binding proteins (VDBP) 50 , 51 . Estrogen components in Hormonal contraceptives has been shown to increase the production of VDBP in the liver 50 , 52 . VDBP is responsible for transporting vitamin D in the bloodstream, and higher levels of VDBP can lead to increased binding and circulation of vitamin D in the body. As a result, individuals with higher estrogen levels, such as those using hormonal contraceptives, may have higher levels of VDBP and therefore higher serum vitamin D levels. Additionally, estrogen has been shown to have a direct effect on the activity of enzymes involved in vitamin D metabolism. Estrogen can enhance the conversion of vitamin D into its active form, which may also contribute to higher serum vitamin D levels in hormonal contraceptive users 10 . Similarly, it is also hypothesized that hormonal contraceptives might increase absorption of vitamin D in the intestine, and leading to higher levels of vitamin D in the bloodstream 35 .

Opposing results were found in the current study regarding the association between the use of hormonal contraceptives and serum Vitamin D (25(OH)D) levels when compared to previous studies conducted in Iraq 38 and Turkey 37 . These studies suggested that the use of hormonal contraceptives may have no effect on serum Vitamin D levels, or even lead to a decrease in the mean level of Vitamin D among users. The conflicting results between our study and the studies from Iraq and Turkey may be attributed to factors such as differences in study populations and methodologies. For instance, the study from Turkey focused on women with polycystic ovary syndrome (PCOS), a condition known to impact Vitamin D levels 53 . The variation in findings between these studies and ours could be explained by the difference in study participants, as our study included individuals without PCOS.

The present study also revealed that Users of combined oral contraceptives (COC) had significantly higher mean serum Vitamin D levels compared to users of Norplant and DMPA, as well as non-users. This finding may partly be explained by the fact that COCs consist of a combination of estrogen and progestin, whereas other classes of hormonal contraceptives are primarily composed of progestin only. Estrogen has been shown to have a potential role in enhancing Vitamin D synthesis and metabolism, which could account for the higher levels observed in COC users. Conversely, progestin-only contraceptives may not have the same effect on Vitamin D levels. This differentiation in hormonal composition may help explain the variability in serum Vitamin D levels among users of different types of hormonal contraceptives. This hypothesis is supported by several previous studies 10 , 13 , 36 , 46 , 47 , 49 , 54 . However, further research is needed to fully elucidate the underlying mechanisms responsible for these differences.

On the present study the prevalence of Vitamin D deficiency (< 20 ng/ml) among hormonal contraceptive users was found to be 21.6% (15.90–28.65), whereas 48.14% (40.50–55.87) of non-user controls had vitamin D deficiency. This finding is consistent with previous studies from Norway (17%) 43 and the United States (19.1%) 46 which reports hormonal contraceptive users have lower vitamin D prevalence. This may be explained by the action of Estrogen to have a potential role in enhancing Vitamin D synthesis and metabolism, which could account for the higher levels observed in among HC users 10 . It can also further elucidate that better compliance with healthcare recommendations among women on hormonal contraceptives; this is because women who use hormonal contraceptives may have more consistent interaction with the healthcare system, including regular visits to their healthcare providers for prescription refills and check-ups. During these visits, healthcare providers may discuss the importance of maintaining adequate vitamin D levels and provide recommendations for achieving this, such as dietary changes or supplementation. This increased engagement with healthcare services may help women using hormonal contraceptives better manage their health, including their vitamin D status 15 , 54 .

In contrast, the reported prevalence of Vitamin D deficiency among hormonal contraceptive users on the current study 21.6% (15.90–28.65), is lower than previous reports from Italy (35%) 42 and Canada (50%) 31 , but higher than result from Uruguay 49 and United state 10 ; The differences in prevalence rates across these studies may be attributed to several factors, including variations in study design, participant and other environmental factors. These variations may influence the prevalence of vitamin D deficiency among hormonal contraceptive users in different populations. Our study was also conducted in dry season considering high exposure to sunlight unlike other studies which did not consider these factors.

On the current study the the odds of having Vitamin D deficiency were 2.99 times higher among participants who attained higher education. This may be due to the reason that Individuals with higher education levels may have sedentary lifestyles or spend more time indoors due to their occupations, which can limit their exposure to sunlight, the primary source of Vitamin D. Lack of sunlight exposure can contribute to Vitamin D deficiency 55 . Conversely, Participant who never eat fish shown to have increased odds of having Vitamin D deficiency by 12.36 times. This may elucidate by the fact that Fish, especially fatty fish like salmon, tuna, and mackerel, are rich sources of Vitamin D. By never consuming fish, individuals are missing out on a significant dietary source of Vitamin D, which can lead to deficiency 56 . On the other hand, Participants who reported to have never been used vitamin D Supplements was observed to have 4.1 times higher odds of having Vitamin D deficiency. This finding is in line with previous report from United state 10 which state consumption of vitamin D containing supplements was positively associated found a positive association between consumption of vitamin D-containing supplements and serum total Vitamin D levels supports the current finding. Using vitamin D supplements can increase the amount of Vitamin D in the bloodstream, thereby improving total serum Vitamin D levels and reducing the risk of deficiency 57 .

On the present study, the utilization of combined oral contraceptives (COC) shown to reduce the risk of vitamin D deficiency by 90% (AOR 0.10 95% CI (0.02–0.36, p 0.000); this is agreement with previous reports from studies conducted among COC users 31 , 33 , 38 , 43 , 46 , 47 , 49 . This finding may be explained the presence of higher concentration of estrogen in a combination of progestin in COC. Although the exact molecular mechanism is still unclear Estrogen, has been shown to potentially play a role in enhancing the synthesis and metabolism of Vitamin D in the body and thus leading to higher levels of Vitamin D in individuals who use COCs that contain estrogen 34 .

The odds of having Vitamin D deficiency shown to be lower among participants with normal serum calcium concentration (AOR 0.50 (0.26–0.97)) and Hypercalcemic state with AOR 0.31 (0.10–0.99); this is in line with previous reports 38 , 49 . Vitamin D plays a crucial role in regulating calcium levels in the body. It helps in the absorption of calcium from the intestines and maintains calcium levels in the blood within a narrow range. If there is a deficiency of vitamin D, it can lead to decreased calcium absorption and levels in the blood, potentially causing weak and brittle bones 49 , 58 .

On the current study we found the use of hormonal contraceptive use may affect Vitamin D levels. The mean serum Vitamin D levels were higher among combined oral contraceptive (COC) users compared to Norplant and DMPA users and non-users. The prevalence of Vitamin D deficiency was lower among hormonal contraceptive users, particularly those using COCs, compared to non-users. Factors such as higher education, lack of fish consumption, and not using vitamin D supplements were associated with higher odds of Vitamin D deficiency. Additionally, individuals with normal and hypercalcemia state had lower odds of Vitamin D deficiency.

Recommendations

Based on the findings of this study, it is recommended that healthcare providers consider monitoring Vitamin D levels in individuals using hormonal contraceptives, especially those using Norplant and DMPA. Education and counseling on the importance of consuming fish and taking vitamin D supplements should be provided to individuals at risk of Vitamin D deficiency. Further research is needed to explore the mechanisms underlying the relationship between hormonal contraceptive use and Vitamin D levels, as well as the potential benefits of COCs in reducing the risk of Vitamin D deficiency. Additionally, public health interventions should be developed to improve awareness and access to Vitamin D supplementation for individuals at risk of deficiency.

Strength and limitation of the study

Strength of the study.

It is the first study in Ethiopia to assess serum vitamin D level of Hormonal contraceptive users and among a few in worldwide. The Comparative study design nature of the current study and by comparing the Vitamin D levels and prevalence of deficiency among hormonal contraceptive users and non-users, we were able to identify some potential relationship. Large sample size: The study included 324 participants, which increases the generalizability of the findings. The current study also considered factors such as sociodemographic, behavioral and clinical as well as diet characteristics and calcium levels in the analysis, which strengthens the validity of the findings. All the laboratory analysis is performed in referral hospital laboratory which increase the quality of the data obtained.

Limitation of the study

Even though we incorporate a reference control group on the current study; the study design limits the ability to establish causality between hormonal contraceptive use and Vitamin D levels. We also use a self-reported data and the reliance on self-reported data for factors such as fish consumption and supplement use may introduce recall bias. The current study also conducted purposefully in a limited geographic scope. Due to unavailability of these assays serum ALP was analyzed without identifying bones specific ALP. The study was conducted in a specific region (Gondar Town), which may limit the generalizability of the findings to other populations.

Data availability

Most of data generated or analyzed during this study are included in this published article; and Addition research data set associated with a paper is available, can be accessed in contact with corresponding author.

Abbreviations

25-hydroxycholecalciferol

Alkaline phosphate

Analysis of variance

Body Mass Index

Blood pressure

Confidence interval

Combined oral contraceptives

Contraceptive prevalence rate

Diastolic blood pressure

Depo-medroxyprogesterone acetate

Ethinylestradiol

Ethiopian Birr

• Hormonal contraceptives

Polycystic ovary syndrome

Systolic blood pressure

University of Gondar Comprehensive Specialized Hospital

Vitamin D binding proteins

Waist to Hip ratio

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Acknowledgements

We would also like to express our gratitude to the participants for being voluntary to participate in the study and generously shared their time and experiences for this study. We would like to acknowledge UOGCSH Clinical chemistry laboratory staffs for their support and laboratory analysis that made this research possible. Special thanks to data collectors for their assistance with data collection.

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E.C. conceptualized and designed the study, including the research question, study design, and data collection methods. E.C., B.B.T. and D.M.B. was responsible for overseeing the data collection process, ensuring adherence to study protocols, and verifying data accuracy. E.C., B.B.T., D.M. and A.M. conducted the statistical analysis, interpreted the results, and contributed to the writing of the methodology and results sections of the manuscript; and assisted in the interpretation of the results, provided critical feedback on the manuscript drafts, and revised the final version of the manuscript. E.C., M.T., Z.Y., A.A.A. contributed to the literature review, study background, and discussion sections of the manuscript. E.C., B.B.T., D.M. and N.C. was involved in the study conception and design, data analysis, and interpretation of the findings, as well as providing overall supervision of the project.

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• Published: 27 September 2024

A comparative study of the application of three digital imaging techniques to assess the thickness of the palatal mucosa of the maxillary anterior teeth

• Shaoqing Sun 1 ,
• Yue Wang 1   na1 ,
• Zikai Gong 1 ,
• Wenxi Zhao 1 ,
• Linglu Jia 1 &
• Yong Wen 1  

BMC Oral Health volume  24 , Article number:  1137 ( 2024 ) Cite this article

Metrics details

This study highlights the need for precise and efficient methods to measure palatal mucosal thickness in the maxillary anterior teeth, particularly for soft tissue augmentation in the aesthetic zone. The research evaluates three digital imaging techniques, suggesting that Cone Beam Computed Tomography (CBCT) combined with intraoral scanners (IOS) is a promising approach for reliable clinical assessment.

Ten volunteers with healthy periodontium were selected, and three methods were employed: CBCT-based indirect gingival imaging, modified soft tissue CBCT (ST-CBCT), and CBCT combined with IOS. Measurements of palatal mucosal thickness were taken at multiple points along the palatal gingival margin. Statistical analysis included Bland-Altman plots for method agreement and intraclass Correlation Coefficient (ICC) analysis for reliability. All measurements were standardized, repeated for consistency, and accurate to 0.01 mm to ensure reliability.

The Bland-Altman plots showed that less than 5% of the points for palatal mucosal thickness differences measured by the gingival indirect radiographic method, modified ST-CBCT, and CBCT combined with IOS were located outside the 95% limits of agreement (LoA). The mean value of the differences was within 0.2 mm, indicating good clinical agreement among the three methods. The inter- and intra-study ICC values for palatal mucosal thickness measurements of the maxillary anterior teeth using the three CBCT methods were greater than 0.75 ( P  < 0.001), demonstrating reproducibility.

Conclusions

Based on the evaluation of three digital imaging techniques, this study indicates that the combination of CBCT with IOS is a feasible method for measuring palatal mucosal thickness in the maxillary anterior teeth and demonstrates good reproducibility.

Peer Review reports

Implant restorations have traditionally prioritized peri-implant bone tissue, with the quality and quantity of hard tissue serving as primary success indicators. However, tooth loss and alveolar bone resorption frequently result in soft tissue defects. Research shows that inadequate keratinized mucosa width (KMW) around implants is associated with plaque accumulation, tissue inflammation, and gingival recession, which jeopardize long-term success [ 1 , 2 , 3 ]. Moreover, sufficient mucosal thickness (MT) is crucial for maintaining peri-implant health and aesthetics [ 4 ]. Neglecting these soft tissue components can lead to peri-implant soft tissue dehiscence/deficiency (PSTD), severely compromising the aesthetic outcomes of implants [ 5 , 6 , 7 , 8 ]. Particularly in the aesthetically sensitive maxillary anterior region, implant success criteria now encompass not only osseointegration and functional stability but also long-term aesthetic outcomes [ 9 ], achieving a higher Pink Esthetics Score (PES) [ 10 ] and White Esthetics Score (WES) [ 11 ]. Advancements in CAD/CAM technology ensure precise, lifelike restorations, yet superior PES demands healthy, coordinated gingival aesthetics, particularly challenging in maxillary anterior implants.

To address issues related to peri-implant soft tissue, augmentation procedures have been developed to limit marginal bone loss and reduce the incidence of bleeding on probing, thereby maintaining and enhancing peri-implant health [ 6 ]. In the maxillary anterior aesthetic zone, thicker mucosa can effectively reduce the risks of soft tissue recession, color mismatch, and implant exposure [ 12 , 13 ]. The palatal connective tissue flap rotation, a pedicled flap technique, enhances mucosal thickness while preserving blood supply to the donor site, thereby minimizing postoperative discomfort and accelerating healing [ 14 , 15 ]. In this region, the adequacy of palatal mucosal thickness directly impacts the success and aesthetic outcomes of the pedicled flap. Achieving these aesthetic standards requires accurate measurement of oral mucosal thickness, which is crucial for planning and executing soft tissue augmentation procedures. Standard clinical methods for measuring oral mucosal thickness include the perforated gingival method [ 16 , 17 ], the ultrasonic method [ 18 , 19 , 20 , 21 ], and the radiographic method [ 22 , 23 , 24 , 25 ]. Each method has pros and cons, and there is no consensus in clinical practice and research on the most accurate method for peri-implant mucosal thickness.

Cone-beam computed tomography (CBCT) is primarily used for hard tissue imaging, but soft tissue overlap often causes blurred image boundaries. To address this, new non-invasive techniques such as the “tray method“ [ 26 ] and Soft Tissue Cone-Beam Computed Tomography (ST-CBCT) [ 22 , 23 , 27 ] have been developed. The “tray method” involves the patient wearing a tray containing a mixture of contrast agent and alginate impression material, while the “ST-CBCT” method requires the patient to use a cotter and tongue depressor during CBCT imaging, followed by soft tissue thickness measurements. However, these methods are cumbersome, time-consuming, and uncomfortable for patients. Conversely, intraoral scanners (IOS) can swiftly and accurately capture the three-dimensional morphology of teeth and surrounding soft tissues, enhancing clinical efficiency and providing precise data for subsequent digital design and analysis [ 28 , 29 ].

The objective of this study is to compare the efficacy of three digital imaging techniques in assessing palatal mucosal thickness in the maxillary anterior teeth, with a particular focus on the accuracy and reliability of the CBCT combined with IOS method in soft tissue augmentation procedures within the aesthetic zone.

Sample selection

This study included 10 student volunteers, 4 males and 6 females, enrolled at Shandong University and aged between 22 and 27 years. The study received approval from the Ethics Committee of School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University (20200502), and adhered to the principles of the Declaration of Helsinki. All volunteers were required to read, understand, and sign an informed consent form, which provided a comprehensive explanation of the study’s design and purpose. The sample size was calculated using G*Power software and is based on the anticipated differences in palatal mucosal thickness. Based on our preliminary findings, the average mucosal thickness measured by three methods was (2.60 ± 0.58) mm, (2.92 ± 0.64) mm, and (2.71 ± 0.59) mm, respectively. With a significance level of 0.05 and a power of 0.80, repeated measures ANOVA determined that the minimum required sample size is 9 participants. Therefore, this study included 10 participants and 60 measured teeth.

Inclusion criteria: all subjects had a healthy periodontal condition with a periodontal probing depth of no more than 3 mm, a bleeding index of ≤ 2 (according to the bleeding index criteria proposed by Mazza in 1981), no gingival recession in the maxillary anterior teeth, and no restorations in the mouth that could interfere with CBCT imaging.

Exclusion criteria: pregnant or lactating females; maxillary anterior teeth with fillings or crowns; misaligned teeth; use of any medications affecting soft tissues; smoking; history of orthodontic treatment; iodine allergy; and systemic diseases that could interfere with the experimental results. Each subject received oral hygiene maintenance instructions and underwent a dental cleaning one week prior to testing.

Method 1 (M1): CBCT-based indirect gingival imaging method [ 26 ]

The same specialized dental imaging practitioner used a CBCT device (New Tom 5G, Italy) to take CBCT photographs of ten subjects, utilizing CBCT-based gingival indirect radiography (Fig.  1 ) and measuring the maxillary anterior region (segments 13 to 23). We made preliminary impressions with silicone rubber to fabricate custom trays before imaging, employing the “tray method.” After stabilizing the silicone rubber, these trays were evenly trimmed with a scalpel to provide an approximate 2 mm gap with the gingival tissue. We made the final impression by mixing iodine developer with alginate impression material, then placing it on the subjects’ teeth to ensure close contact with the tooth and gingival surfaces. All scans were performed at 110 kV and 10 mA for 18 s (voxel size: 0.3 mm; grayscale: 16 bits; focal spot: 0.3 mm; and field of view: 18 × 16 cm).

CBCT-based indirect gingival imaging method. ( A ) Individualized trays for zones 13 to 23 were crafted from silicone rubber. ( B ) The trays were meticulously trimmed to maintain a gap of approximately 2 mm from the gingival tissue

Method 2 (M2): Modified ST-CBCT [ 23 ]

We used a cotter and tongue depressor to separate the upper lip and tongue tissues from the labio-palatal lateral gingiva of the maxillary anterior teeth, employing a modified ST-CBCT method (Fig.  2 ). CBCT data were imported into T3DView in “.dicom” format. Adjustments to contrast and sharpness were made to delineate gingival tissues. The tooth was positioned, and the sagittal plane was used to measure palatal mucosal thickness (Fig.  3 ).

Modified ST-CBCT

Standardized adjustments using T3DView software: ( A ) Axial plane; ( B ) Sagittal plane; ( C ) Coronal plane

Method 3 (M3): CBCT + IOS measurements

We measured the soft tissue images of the oral cavity obtained by IOS after aligning them with the hard tissue images generated by CBCT, without any interventions. IOS was performed by experienced technicians using an intraoral scanner (TRIOS, 3Shape, Copenhagen K, Denmark). The chair position for the oral scanner was based on principles of comfort and ease of operation for both patient and clinician. Preparation ensured a clear field of view without contamination by saliva, food debris, or blood. Tooth surfaces were dried and equipped with a saliva suction device. An optical impression of the subject’s maxillary dentition was taken in the same scanning sequence (occlusal-palatal-labial) under natural light. The data were saved and exported in “.stl” format. The CBCT data of the subject, in “.dicom” format, were imported into the implant guide software SIMPLANT Pro 17.01. Thresholds of [800, 3071] were selected, and then the data were segmented, preserving the hard and soft tissues in the maxillary anterior region. The data were then exported into “.stl” format and imported into the IOS. Marker points of the same teeth in both CBCT and IOS data were selected for alignment. A preliminary rough alignment was conducted by manually selecting six reference points on the teeth, specifically the mesial buccal tips of the bilateral first molars, the buccal tips of the first premolars, and the incisal edges of the central incisors. Following rotational translation based on these reference points, the registration process was confirmed by examining the alignment contours of the data (Fig.  4 ). After fitting, we performed the same standardized adjustment of the CBCT image and measured the palatal mucosal thickness in the sagittal plane of the tooth.

Importing data into SIMPLANT Pro 17.01: ( A ) Importing CBCT data in “.dicom” format for subjects in SIMPLANT Pro 17.01. ( B ) Importing IOS data in “.stl” format for subjects in SIMPLANT Pro 17.01. ( C ) Aligning and fitting the subject’s CBCT data to the IOS data

In all three aforementioned methods, the measurement of mucosal thickness adhered to the same principles. The palatal mucosal thickness was measured with reference to studies by Song [ 30 ] and colleagues. Measurement sites were selected at 2 mm, 4 mm, 6 mm, 8 mm, 10 mm, and 12 mm from the apex of the palatal gingival margin of the maxillary anterior teeth (Fig.  5 ). The vertical distance from the mucosal surface to the bone surface at these sites was recorded as the mucosal membrane thickness (Fig.  6 ).

Measurement site pattern diagram

Measurement of lateral palatal mucosal thickness through three distinct methods. Method 1: A - C , Method 2: D - F , Method 3: G - I

Ten subjects had their CBCT images measured using the three methods, yielding a total of 1080 loci, with 36 loci per subject per measurement method. As shown in Fig.  5 , the three previously mentioned methods align and measure along the tooth’s long axis to reduce intergroup errors. All values were accurate to 0.01 mm to minimize measurement bias and enhance data reliability. Two trained researchers conducted the measurement process using the same equipment, with two measurements taken within 24 h to assess consistency, and the average value was recorded.

Statistical analysis

Bland-Altman plots were produced using GraphPad Prism version 8.0.1 software to analyze the agreement between the results of the three CBCT methods for measuring the palatal mucosal thickness of the maxillary anterior teeth. The Bland-Altman plots calculate the mean difference between measurements; the closer the mean is to zero, the better the agreement. IBM SPSS Statistics 26.0 software performed an intraclass Correlation Coefficient (ICC) analysis to evaluate inter-investigator and retesting reliability. Generally, the ICC value ranges from 0 to 1. An ICC value less than 0.4 indicates poor repeatability, while an ICC value greater than 0.75 indicates excellent repeatability.

The mean mucosal thicknesses measured by the three CBCT methods were (2.61 ± 0.71) mm, (2.69 ± 0.73) mm, and (2.77 ± 0.71) mm, respectively. GraphPad Prism 8.0 software was used to produce bar graphs of the palatal mucosal thicknesses of the maxillary anterior teeth measured by the three methods (Fig.  7 ).

Mean thickness of the palatal mucosa of the maxillary anterior teeth measured by three methods

We used SPSS 26.0 software for ICC analysis (Table  1 ). For M1, the inter-investigator reliability was 0.960 and the retest reliability was 0.979; for M2, the inter-investigator reliability was 0.959 and the retest reliability was 0.979; and for M3, the inter-investigator reliability was 0.934 and the retest reliability was 0.966. The palatal mucosal thicknesses of the maxillary anterior teeth, measured by all three CBCT methods, had intra- and inter-investigator ICC values greater than 0.75 ( P  < 0.001), indicating that all three measurements were reproducible.

GraphPad Prism 8.0 software was used to produce Bland-Altman plots (Fig.  8 ). The analysis indicates that the differences between measurements are as follows: M1 vs. M2: (-0.082 ± 0.38) mm, with a 95% limits of agreement (LoA) ranging from − 0.83 to 0.66 mm, and 3.61% of points outside this range; M1 vs. M3: (-0.16 ± 0.41) mm, with a 95% LoA from − 0.96 to 0.64 mm, and 4.44% of points outside; M2 vs. M3: (-0.076 ± 0.45) mm, with a 95% LoA from − 0.95 to 0.8 mm, and 5% outside the range. The pairwise differences in palatal mucosal thickness measurements of the maxillary anterior teeth by the three methods had fewer than 5% of points located outside the LoA range, with mean differences within 0.2 mm, indicating good clinical agreement among the three methods.

Consistency analysis of three CBCT imaging methods for measuring palatal mucosal thickness in maxillary anterior teeth. ( A ) Measurement Results of M1 and M2. ( B ) Measurement Results of M1 and M3. ( C ) Measurement Results of M2 and M3

This study confirmed the effectiveness of using CBCT combined with IOS to measure palatal mucosal thickness in the anterior maxillary region, revealing that this method is efficient, accurate, non-invasive, and reproducible in clinical applications. Compared to the “tray method” and the modified ST-CBCT method, CBCT combined with IOS offers highly consistent measurement results, with an average difference of less than 0.2 millimeters, indicating strong clinical agreement among the three methods. Furthermore, the study reveals that the ICC for palatal mucosal thickness measurements across all three methods exceed 0.75 ( P  < 0.001), signifying their high reliability upon repeated use.

In certain cases, alternative measurement methods are still utilized. The transgingival probing technique, performed under local anesthesia, is quick and requires no specialized equipment, but its invasiveness often causes significant patient discomfort, limiting its use to intraoperative settings. Local anesthesia may also increase soft tissue volume, and the probe’s sliding rubber stopper can introduce measurement errors [ 16 ]. Ultrasonic evaluation, a non-invasive method, measures gingival thickness by calculating ultrasonic wave propagation time. While devices with 0.1-millimeter resolution are effective and reliable, they struggle with precise repositioning for repeated measurements [ 18 ]. Additionally, the sensor probe’s limitations reduce its effectiveness in assessing palatal mucosa [ 21 ]. Magnetic resonance imaging (MRI), though preferred for head and neck imaging due to its ability to visualize soft tissues without ionizing radiation, is not widely used in dentistry because of its high cost [ 25 ]. CBCT is widely used in dental radiology, with studies confirming its accuracy and non-invasive nature for imaging and assessing maxillofacial soft tissue thickness [ 27 , 31 , 32 , 33 , 34 ]. Although minor discrepancies may occur when using CBCT alone to measure palatal mucosal thickness, the application of adjustment algorithms and conversion formulas allows its effective use in non-invasive clinical evaluations [ 35 ]. As imaging technology advances, digital methods are increasingly prevalent in preoperative planning and soft tissue measurement for dental implants [ 36 ]. Integrating CBCT with IOS data enables precise acquisition of soft tissue contours [ 37 ], allowing accurate three-dimensional measurement and analysis of both hard and soft tissues. Research shows that linear measurements from CBCT imaging and intraoral scanners are highly valid and reproducible [ 38 , 39 , 40 , 41 ]. By combining data from diverse imaging sources, this digital approach significantly enhances measurement accuracy, particularly for complex assessments such as gingival height and other periodontal biotypes [ 42 ]. Ferry et al. compared direct contact methods, CBCT scanning, and the digital method combining CBCT with IOS, finding that the digital approach showed the highest consistency with histological measurements [ 43 ]. Recent reviews reinforce the potential of these technologies, highlighting the non-invasive benefits of digital techniques like CBCT combined with IOS, especially for evaluating and monitoring peri-implant soft tissue health and aesthetics. The reviews also emphasize that technologies such as ultrasound and spectrometry can monitor soft tissue changes over time, providing clinicians with precise data to optimize treatment planning and execution [ 44 ]. The alignment accuracy between CBCT and IOS data is 0.2 mm [ 45 ], meeting clinical requirements. Additionally, this data can be stored, transmitted, analyzed, and shared, offering a more streamlined method for evaluating soft tissue thickness [ 46 ].

From a clinical perspective, accurate measurement of palatal mucosal thickness is essential for soft tissue grafting in aesthetic zones, as factors like age and gender can influence thickness and impact surgical decisions [ 47 ]. Studies show that palatal soft tissue around implants is significantly thicker than around natural teeth, with thicker tissue linked to deeper periodontal pockets and more severe peri-implantitis [ 48 ]. These findings highlight the need for personalized tissue thickness assessment to improve surgical planning and optimize aesthetic and functional outcomes.

This study focused on the palatal mucosa thickness in the maxillary anterior region, a crucial area in implant aesthetics. Given the aesthetic demands, this region is often selected for soft tissue grafting, leading to the development of various augmentation techniques. One technique, proposed by Abrams [ 14 ], addresses mild to moderate soft tissue defects by advancing a pedicled partial-thickness flap from the palatal side. This involves removing the keratinized layer to expose the connective tissue, which is then advanced under the labial tissue to enhance thickness. Scharf and Tarnow refined this method by preserving a thin epithelial layer at the donor site, promoting primary healing and reducing patient discomfort [ 15 ]. Studies have shown this technique achieves an average PES score of 11.7 at the implant site, with no significant postoperative changes, confirming its aesthetic efficacy [ 49 ]. For severe defects, the Vascularized Interpositional Periosteal Connective Tissue (VIP-CT) flap, introduced by Sclar, is recommended [ 50 , 51 ]. This method folds a periosteal-connective tissue flap from the palatal area and inserts it under the labial mucosa, ensuring a stable blood supply, reducing tissue shrinkage, and achieving optimal gingival contours. The VIP-CT flap is covered by labial soft tissue, preserving natural gingival color and texture, resulting in superior aesthetics and minimizing the need for secondary surgeries [ 52 ]. Moreover, compared to the free epithelialized subepithelial Connective Tissue Graft (CTG), VIP-CT better maintains augmented tissue volume within six months postoperatively, owing to enhanced blood perfusion, which improves graft stability and long-term outcomes [ 53 ]. Compared to other palatal regions, the anterior palate has thinner soft tissue, making it more susceptible to resorption, thus limiting its use as a donor site. Three-dimensional analyses show that the posterior palate has significantly greater tissue thickness, reinforcing its preference for soft tissue surgeries [ 54 ]. Selecting the appropriate grafting technique and donor site is crucial, with the ultimate goal being the success of the dental implant [ 53 , 55 ]. When evaluating the anterior versus posterior palate for soft tissue surgery, key factors such as tissue thickness, blood supply, aesthetic outcomes, and postoperative recovery must be considered. The posterior palate is favored for its thicker tissue and lower risk of graft shrinkage, while the anterior region, though offering a better aesthetic match, is limited by its thinness. Therefore, technique selection should be carefully tailored to specific aesthetic needs and soft tissue conditions to ensure optimal clinical outcomes and patient satisfaction.

While this study validated the efficacy of using CBCT combined with IOS to measure palatal mucosa thickness in the maxillary anterior region, it has several limitations. The small, specific sample size may not represent the soft tissue characteristics of diverse ethnicities and age groups. The study also focused only on maxillary anterior teeth, omitting premolars, molars, and mandibular teeth. Measurement accuracy depended on equipment precision and operator skill [ 56 ]. Despite repeated measurements to enhance reliability, operational errors remain possible. Future research should expand sample size, include diverse populations, and broaden measurement sites to better validate the method’s generalizability. Continued optimization of the measurement process and exploration of automated analysis tools are necessary to enhance efficiency, reduce errors, and improve the standardization of peri-implant soft tissue management.

Through evaluating three digital imaging techniques, this study demonstrates that CBCT combined with IOS is a feasible method for measuring the palatal mucosal thickness of maxillary anterior teeth and offers an efficient, accurate, non-invasive, reproducible, and reliable approach for clinical assessment.

Data availability

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

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Acknowledgements

Supporting this study, heartfelt gratitude is extended to Dr. Li Guoju and Dr. Yu Jian from the Department of Radiology, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University for their invaluable support and assistance.

Funded by Clinical Research Center of Shandong University (No. 2020SDUCRCC006) and Natural Science Foundation of Shandong Provincial (No. ZR2021MH075).

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Shaoqing Sun and Yue Wang contributed equally to this work.

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Department of Implantology, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, No.44-1 Wenhua Road West, Jinan, Shandong, 250012, China

Shaoqing Sun, Yue Wang, Zikai Gong, Wenxi Zhao, Linglu Jia & Yong Wen

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S.S. and Y.W. were responsible for conceptualization and methodology. Data curation and analysis were performed by Z.G. and W.Z. Y.W. provided supervision, while the manuscript was written and edited by S.S., L.J., and Y.W. All authors have reviewed and approved the final version of the manuscript for publication.

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The study received approval from the Ethics Committee of School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University (20200502) and adhered to the principles of the Declaration of Helsinki. All participants provided their informed consent prior to their involvement in the study.

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Sun, S., Wang, Y., Gong, Z. et al. A comparative study of the application of three digital imaging techniques to assess the thickness of the palatal mucosa of the maxillary anterior teeth. BMC Oral Health 24 , 1137 (2024). https://doi.org/10.1186/s12903-024-04896-1

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DOI : https://doi.org/10.1186/s12903-024-04896-1

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Enhancing Tonsillectomy Recovery with AI: A Comparative Study on Postoperative Care Outcomes

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• Sanjay Kumar   ORCID: orcid.org/0000-0002-9737-7327 1 ,
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Introduction: Tonsillectomy is commonly associated with significant postoperative challenges such as pain management, complication monitoring, and patient recovery. Traditional care methods, while effective, often do not adequately address these issues, particularly in personalized care and remote monitoring. This study assesses the impact of Artificial Intelligence (AI)-assisted postoperative care on recovery outcomes in tonsillectomy patients compared to conventional care methods. Methods: Conducted at a tertiary care hospital’s Otolaryngology Department from January to December 2023, this observational cohort study involved 100 elective tonsillectomy patients. Participants were divided into two cohorts: one receiving traditional care and the other AI-assisted care, which utilized machine learning for pain management, continuous symptom monitoring through wearable devices, and virtual assistance. Results: AI-assisted care significantly improved early postoperative pain management, reducing pain scores to 5.2 ± 1.1 from 6.5 ± 1.2 in traditional care ( p  = 0.01). Dehydration rates decreased from 6 to 1% ( p  = 0.05), and the average hospital stay was reduced to 2.8 ± 1.1 days from 3.5 ± 1.2 days. While no significant differences were found in readmission rates for haemorrhage and infection, patient satisfaction notably increased, with pain management improving to 4.4 ± 0.7 and overall satisfaction to 4.1 ± 0.6 ( p  = 0.03). Conclusion: AI-assisted care offers significant advantages over traditional methods in managing tonsillectomy recovery, optimizing surgical outcomes, and enhancing patient satisfaction. This study supports further exploration into AI’s long-term outcomes and its application across various surgical fields.

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Acknowledgements

We would like to express our gratitude to our patients, their parents/guardians, the committed medical and administrative personnel of Command Hospital Air Force, Bangalore, India, for their consistent support and assistance during the duration of the study. The present study was supported by self-funding, and we express our gratitude to those individuals who, via personal financial resources and unwavering commitment, facilitated the execution of this research.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. There are no material financial or non-financial interests to disclose for the authors.

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Sanjay Kumar & Anghusman Dutta

Department of Anaesthesia, Command Hospital Airforce, Rajiv Gandhi University of Health Sciences, Bangalore, India

Manish Gupta

Department of Medicine, Army College of Medical Science, Delhi Cantt, Delhi, India

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About this article

Kumar, S., Dutta, A., Gupta, M. et al. Enhancing Tonsillectomy Recovery with AI: A Comparative Study on Postoperative Care Outcomes. Indian J Otolaryngol Head Neck Surg (2024). https://doi.org/10.1007/s12070-024-05103-x

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Received : 17 April 2024

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