medical term paper

Medical Terminology for Healthcare Professions

(8 reviews)

Andrea M. Nelson, University of West Florida

Katherine Greene, University of West Florida

Copyright Year: 2021

Publisher: University of West Florida Pressbooks

Language: English

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Reviewed by Wendy Schuh, Assistant Professor, Minnesota State University Mankato on 2/8/24

This book is clearly laid out with 18 different chapters covering all of the body systems + obstetrics. There are interactive figures, flash cards, and end of chapter quizzes. Vocabulary words have a linked definition within the text. It would be... read more

Comprehensiveness rating: 5 see less

This book is clearly laid out with 18 different chapters covering all of the body systems + obstetrics. There are interactive figures, flash cards, and end of chapter quizzes. Vocabulary words have a linked definition within the text. It would be an added benefit to include pronunciation, which is an important component of medical terminology. Videos have a captioning option.

Content Accuracy rating: 5

No concerns with accuracy.

Relevance/Longevity rating: 5

References are included with each chapter. Publication date is 2021, and most references are within the last five years. In addition, this content is mostly stable over the years. CrashCourse videos are a little older (2015) but many students are familiar with Hank Green in this format. Information is relevant and easy to process.

Clarity rating: 5

Clear chapter content, sections, and headings.

Consistency rating: 5

Consistent style of writing, activities, page layout, etc. throughout the book.

Modularity rating: 5

Chapters organized in a logical manner. Flashcards and interactive body part activities are wonderful tools, even better since they can be completed multiple times.

Organization/Structure/Flow rating: 4

The structure of the textbook is sound and consistent with other medical terminology textbooks. A more thorough Table of Contents would allow for easier navigation. It has a good balance of technical and non-technical writing that makes it easy to read and comprehend.

Interface rating: 3

Appealing and interactive. I attempted to take advantage of the “re-use” option below each activity but could not figure it out. Search function does not work well. I tried searching phrases directly from the text, and it would not pull up. The labeling activities were difficult to complete as the drag and drop feature would not scroll. Therefore, it would be useful to have a correct answer option to see the completed figure. It would be helpful to have descriptions included with different e-book options that explain interactive functions with each format.

Grammatical Errors rating: 5

Very clean and proofed!

Cultural Relevance rating: 5

Appeared to be culturally inclusive, although it is difficult to assess in this type of resource. No diverse representation of skin color on diagrams.

This is a great textbook that mimics other medical terminology textbooks costing $100+ that don’t have interactive components. There could be some great additions to more effectively use this for a course textbook, such as a question bank, study guides, and suggestions for worksheets and projects to incorporate points into a course framework.

Reviewed by Sharon Schaeffer, Associate Clinical Professor, Bowling Green State University on 4/16/23

Covers major body systems . read more

Covers major body systems .

I did not see any errors during my review.

Medical terminology is a pretty static topic. When students learn how to correctly combine forms, they will be ready to decipher new vocabulary that comes with progress in health care.

Easy to understand.

The depth of content is consistent.

I will allow students to choose their topic of the week after the first 3 chapters are complete. The module system will work well for this design. This design allows students taking A & P or similar courses the opportunity to learn med term at the same time as they are learning in other courses.

Organization/Structure/Flow rating: 5

Well organized.

Interface rating: 5

I had no challenges linking to and using the added features.

No problems noted.

Inclusive content.

This book will help my students learn the basics of medical terminology as a foundation for building a strong professional vocabulary. I like the interactive activities in this book as it helps learners of different styles. It would be a bonus if there were quiz question banks available. It is not enough of a deal breaker to stop me from using this in my course next Spring semester.

Reviewed by Kristin Meyer, Professor, Drake University on 12/15/22

The text comprehensively covers medical terms in each body system, with a couple of introductory chapters. It covers the span of life with a dedicated obstetrics chapter, which I have not seen in other texts. read more

The text comprehensively covers medical terms in each body system, with a couple of introductory chapters. It covers the span of life with a dedicated obstetrics chapter, which I have not seen in other texts.

No inaccuracies identified.

Medical terminology does not easily or often change, but the text could be easily updated from time to time to include new disease states or terms.

No issues with clarity identified.

Each chapter has a consistent format with link to video overview and active learning activities interspersed throughout.

The organization by body system allows an instructor to assign the appropriate amount of content to correspond with course credit hours.

The online version is easy to navigate. The search function doesn't work as I would expect it to.

Interface rating: 4

The online version is easy to navigate. The pdf download has none of the interactive features. It would be nice if the pdf version could somehow include the active learning exercises in each chapter, with an answer key appendix.

No grammatical errors identified.

Does not appear to be culturally insensitive.

I could easily adopt this text for my web-instructed undergraduate medical terminology class. The interactive features are helpful to engage students. A summary quiz at the end of each chapter would be a nice added feature.

Reviewed by Nancy Bouchard, Adjunct Professor, North Shore Community College on 11/14/22

Very well done. read more

Very well done.

Very accurate and not biased.

If updates are needed, they could be added with ease.

Well written text.

Very consistent.

Very user friendly. Easy to read and assign chapters.

Very organized.

I did not encounter any issues.

None noticed.

Not insensitive or offensive.

My only concern is for the student who has no prior exposure to medical terminology, healthcare training or will not have a clinical role in healthcare. I would not want them to get overwhelmed by the depth of detail in each chapter. I would suggest a section in each chapter that contains exercises for students to test their understanding of the subject matter read, practice correctly writing the terms and the like. Visual learning is only one way for students to absorb content. I would have to create ways to test their understanding to be graded using quizzes, a research project, midterm and final exam. I'm on the fence if the content in the textbook is too deep for only needing a basic understanding of medical terms.

Reviewed by Martha Fabian-Krause, Adjunct Clinical Instructor, Rogue Community College on 9/1/22

Systematic flow of each body system to include root word, prefix, suffix, anatomy, physiology, video and practice in each section. Logical to follow. read more

Systematic flow of each body system to include root word, prefix, suffix, anatomy, physiology, video and practice in each section. Logical to follow.

No issues noted. Very accurate.

Timeless interpretation of terminology would make the on line text need updating only if new medical information becomes available.

Detailed explanations of terminology, anatomy and physiology with pertinent examples and word practice at the end of each body system.

Each section is consistent by acknowledging medical diseases, disorders, and procedures related to the root words. Good follow through in each body system.

This on line book can be assigned in a particular order relevant to other class material and does not need to be completed in any particular time frame. Pleasurable reading.

The format of each section (body system) is in a progressive fashion and is put together with a video near the beginning and word games at the end of each section. Good sequencing noted throughout.

Charts are easy to navigate. There is an identical format what is easy to assimilate.

None noted.

No diversive issues noted. Represents the full spectrum of human anatomy and physiology.

Marvelous understanding of the root words, prefix, suffix and detailed anatomy and physiology. The videos and word matches at the end of each section put the meaning crystal clear.

Reviewed by Carla Tobin, Faculty, Century College on 6/17/22

This textbook covers all of the body systems, the word parts and rules, and prefixes and suffixes. read more

This textbook covers all of the body systems, the word parts and rules, and prefixes and suffixes.

This book is very accurate. No discrepancies or errors were noted in the textbook.

Medical terminology is a subject that does not change over the years. As new diseases and technologies arise, they can easily be incorporated into the content.

The language used in the book is clear and pronunciations of the terminology is provided throughout the e-book. This is an easy to read book for high school or college level students.

The chapters are consistent in there format and organization throughout the textbook. It is easy to follow for the student.

The chapters are broken down into sections which make it easy to read. The videos are shown within the textbook, so the user is not taken to another site. One suggestion would be to have a link to the next chapter at the bottom of the page rather than scrolling up to the top to choose the next chapter from the left side menu.

The organization of this textbook is exactly what you would expect for a Medical Terminology textbook. It is divided into chapters by body system.

There are no apparent issues with the interface. As noted above, the videos are shown within the textbook window, so the user is not taken to another site.

I did not note any grammatical errors in this textbook.

Cultural sensitivity is not really relevant with medical terminology. This language is used in many countries in order to be able to communicate in the same language.

I agree that the best use of this book in the online internet version. This is a very comprehensive medical terminology book. It covers all of the body systems and word building of medical terminology. The chapters provide many opportunities to practice what the student has learned. I liked that each chapter has the learning objectives listed at the beginning. I would have liked to see chapter summaries for the students to study. I think that this book could easily be incorporated into an online class, however, some work would be involved making PowerPoints, homework and quizzes. Overall, this is an excellent Medical Terminology book.

Reviewed by Renee Eaton, Advanced Instructor, Undergraduate Director, Virginia Tech on 5/17/22

Systems-based organization and includes all body systems. read more

Systems-based organization and includes all body systems.

No errors or issues noted

Medical terminology is something that rarely changes. Context activities may change over time, as does disease prevalence and knowledge, but new terms or different terms are not common.

Clear descriptions and use of technical and non-technical language.

The organization is the same across each chapter making the book easy to access and navigate. Language and flow are consistent.

Text is easy to navigate. It may be helpful to provide some in-chapter navigation on the lower menu bar. For example, the previous and next chapters are linked on the left and right margins of the bottom, and chapter components such as diseases / anatomy / etc. could be added to the center. It may not all fit, but even having a couple of navigation points within the chapter would be helpful.

Good organization and order of chapters.

This is one of my greatest difficulties. Navigation within chapters would be helpful. The incorporation of activities, particularly the labeling activities and Medical Terms in Context, are difficult with a regular laptop screen. The text and answer selections are often not on the same screen, making the activity more tedious to complete. Some of the labeling activities also have large images that put the image and answer selections on different screens. The "Did You Know", "Objectives" and colored boxes contain wasted space. They're excessively large especially in the header, and when viewing on a laptop is often half the screen if not more. The PDF version often has issues of inconsistent font size and misalignment of tables.

No grammatical errors found. I appreciated the bold and linked words, with the ability to see definitions with one click. It might be helpful to have a sidebar with the important words and definitions / information in the section, but that might not be feasible with formatting.

Hard to assess for medical terminology.

The best way to use this text is online with solid internet. The PDF version is frustrating as there are no activities or practice opportunities, and there are issues with the organization and appearance such as misaligned tables and font size differences. When internet is good but not great, none of the videos are viewable. The activities and practice opportunities in the online book are very helpful and enjoyable. Their length is appropriate to encourage use and they are strategically placed throughout the chapters. I did have trouble with the search tool, as things I entered went to the glossary but always included the beginning of the glossary. For example, a search for "diplopia" showed the following:

Abdominal Pertaining to the abdomen (National Cancer Institute, n.d.) Abdominoplasty Surgical repair of the abdomen (National Library of Medicine, 2021) Abduction Moving the limb or hand laterally away from the body, or spreading the fingers or toes (Betts et al., 2013) Abductor Moves the bone away from the midline (Betts et al., 2013) Ablation The Read more » Sensory Systems

Learning Objectives Examine the anatomy of the sensory systems Determine the main functions of the sensory systems Differentiate the medical terms of the sensory systems and common abbreviations Discover the medical specialties associated with the sensory systems Recognize common diseases, disorders, and procedures related to the sensory systems Sensory Systems Word Parts Click on prefixes, Read more »

Overall, the authors did a wonderful job of developing a thorough and practical text. I appreciate the thought that went into the interactive nature of the book and the availability to exercises to practice knowledge.

Reviewed by Debra Minzola, Associate Professor, Bloomsburg University of Pennsylvania on 3/18/22

This textbook is very inclusive in the content area. It not only discusses the word but breaks down medical terminology to help learners to easily decipher the meaning of a medical term . read more

This textbook is very inclusive in the content area. It not only discusses the word but breaks down medical terminology to help learners to easily decipher the meaning of a medical term .

There was no inaccuracies detected throughout the text.

This text is very relevant and will easily be updated if needed.

This is an easy to read text and would be a valuable resource for new learners. The ebook offers videos and learning activities throughout.

The text is internally consistent with an easy to follow framework.

The modules in this text are easy to navigate and locate specialty sections.

This text is clearly organized and easy to navigate.

There is no significant navigation problems or confusing features.

There is clear grammar throughout the text.

There is no offensive content in this textbook or language that can be viewed as culturally insensitive.

Learning objectives are listed at the introduction of each section followed by a guide on how to break down each system's medical terms. Throughout each section there are diagrams, charts, and additional videos in the ebook which reinforces the content. The book is organized and easy to navigate.

Table of Contents

• 1. Word Parts and Rules
• 2. Prefixes and Suffixes
• 3. Body Terminology
• 4. Sensory Systems
• 5. Integumentary System
• 6. Skeletal System
• 7. Muscular System
• 8. Nervous System
• 9. Cardiovascular System
• 10. Blood Vessels and Blood
• 11. Lymphatic and Immune Systems
• 12. Respiratory System
• 13. Digestive System
• 14. Endocrine System
• 15. Urinary System
• 16. Male Reproductive System
• 17. Female Reproductive System
• 18. Obstetrics

Ancillary Material

About the book.

Medical Terminology for Healthcare Professions is an Open Educational Resource (OER) that focuses on breaking down, pronouncing, and learning the meaning of medical terms within the context of anatomy and physiology. This resource is targeted for Healthcare Administration, Health Sciences, and Pre-Professional students.

About the Contributors

Andrea M. Nelson , PT, DPT, GCS, CLT, University of West Florida

Katherine Greene , MPH, University of West Florida

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Why Is Medical Terminology Important?

Medical terminology is the backbone of healthcare communication, promoting accuracy, safety, and efficiency in patient care while facilitating global collaboration and advancing medical science. This standardized language enables healthcare professionals to quickly and accurately assess a patient’s needs and communicate with their care team, resulting in overall better patient outcomes.

The Role of Medical Terminology in Healthcare

When is medical terminology used, who needs to understand medical terminology.

Medical Terminology Examples 

Importance of Knowing Medical Terminology 

How to Improve Your Medical Terminology Skills

Frequently Asked Questions

Medical terminology serves as the universal language that allows healthcare professionals to communicate effectively and accurately. This language consists of official terms and abbreviations that describe anatomy, bodily functions, diseases, diagnoses, treatments, procedures, and more.

It’s important for healthcare professionals — including physician assistants, occupational therapists, and physical therapists — to learn and understand the formal names for medical conditions and procedures. Many terms are often abbreviated for efficiency, lending an additional collection of acronyms to this universal language.

Medical terminology is used extensively and in various contexts throughout the healthcare industry. Not only is it critical in the surgical ward or the emergency room, but it’s also useful for medical receptionists, health insurance agents, health information technicians , and more.

The following are the most common uses for medical terminology:

• Patient care: When used during patient assessments, diagnoses, and treatment planning, medical terminology enables healthcare providers to accurately describe symptoms, conditions, and procedures, ensuring that patient care is well-informed and consistent.
• Medical records: Healthcare facilities maintain detailed medical records for each patient they serve. These records are filled with medical terminology to document a patient’s medical history, medications, lab results, and treatment plans comprehensively.
• Prescriptions: Doctors use medical terminology when writing prescriptions, specifying the medication, dosage, and administration instructions clearly and unambiguously.
• Medical billing: Billing specialists use medical codes to denote conditions, medications, and treatments for a patient’s insurance provider, ensuring that the patient is covered or billed accordingly for the care they receive.
• Consultations and referrals: When physicians consult with specialists or refer patients to other healthcare providers, they rely on medical terminology to convey vital and accurate information about the patient’s condition and requirements.
• Medical imaging: Radiologists and other healthcare technicians use medical terminology to describe findings on X-rays, MRIs, CT scans, and other imaging studies, ensuring precise reporting and treatment recommendations.
• Medical research: Scientists and researchers use medical terminology in scholarly articles, clinical trials, and research papers to share their findings with colleagues and contribute to the global body of medical knowledge.
• Education and training: Medical terminology is a fundamental component of healthcare education. It equips students with the vocabulary needed to understand and communicate effectively in clinical settings.
• Health information systems: Electronic health records (EHRs) and healthcare IT systems rely heavily on medical terminology for data input, retrieval, and exchanges between healthcare providers and facilities.

Of course, it’s critical for doctors, nurses, and those in other clinical roles to understand medical terminology so they can administer proper care and communicate with their colleagues. Aspiring medical practitioners are almost always required to be proficient in medical terminology for admission into graduate programs. It’s even important for some non-clinical healthcare professionals to become familiar with common terms.   

The following individuals are typically required (or at least strongly encouraged) to learn medical terminology.

Clinical roles:

• General practitioners
• Physician assistants
• Medical trainees
• Occupational therapists
• Physical therapists
• Emergency medical technicians (EMTs)
• Emergency responders (911 operators)
• Nursing students & aides
• Social workers
• Home healthcare providers

Non-clinical roles:

• Medical receptionists / office managers
• Medical researchers
• Pharmacists
• Insurance companies
• Billing specialists
• Medical coders
• Healthcare informaticists
• Medical compliance officers

It’s typically not necessary for patients to understand medical terminology; doing so will not affect their care. However, some patients like to understand what certain terms or abbreviations indicate on their charts or in their records, since it helps them feel more engaged in their own care, which can contribute to increased compliance. 

A MEDICAL TERMINOLOGY COURSE IS VALUABLE TO YOUR CAREER

Taking a medical terminology course is a great first step to equip you with the skills and knowledge you’ll need to be successful.

Examples of Medical Terminology

Often, when we talk about health conditions in a non-clinical setting, we use common terms that might describe a collection of symptoms, rather than the formal name for a specific disease, condition, or type of injury. For example, you might tell a coworker that you were out sick with a cold and a bad sore throat; your healthcare provider would have recorded that you had an upper respiratory tract infection (URI) with acute pharyngitis.

Medical terms usually consist of a root word, a prefix, and/or a suffix that lends specificity to the description of a health condition. Many terms originate from Greek or Latin, which is why they might sound unfamiliar or obscure to the untrained ear. Once you become familiar with enough common prefixes, roots, and suffixes, you can begin to understand how the language of medicine is constructed.

Here are five examples of common medical terms, defined and broken into their discrete parts:

• pharyng- = pharynx, or throat
• -itis = disease or inflammation
• ante = before
• cibum = food
• intra- = within
• -venous = relating to a vein
• myo- = muscle
• -cardial = of the heart
• infarction = tissue death
• append- = appendix
• -ectomy = removal

Importance of Knowing Medical Terminology

The ability for all members of a healthcare team to understand and communicate using medical terminology is important for a number of reasons:

It promotes clarity and precision.

Medical terminology eliminates ambiguity by providing precise words and phrases to describe conditions and procedures. This clarity is vital to prevent misunderstandings that could have serious consequences for both patients and care providers.

It standardizes healthcare around the world.

Healthcare is a global industry, and standardized medical terminology ensures that professionals worldwide can understand each other. This is especially important in today’s interconnected healthcare systems.

It supports efficiency.

In fast-paced healthcare settings, concise and standardized language helps healthcare providers save time. It allows for quick, accurate documentation of patient information and facilitates efficient communication between care team members.

It ensures patient safety.

Medical terminology helps prevent errors in diagnoses and treatments by ensuring that everyone involved in a patient’s care understands the same information, reducing the risk of mistakes.

It contributes to furthering medical research.

Medical terminology is the foundation of medical literature and research. It enables healthcare professionals to access, understand, and contribute to ever-expanding medical knowledge.

It supports career advancement.

As with any type of professional and continuing education, building your medical terminology skills can lead to promotions and increase your hireability in the healthcare field. Even if you don’t work in a clinical role, being able to list this as a skill on your resume can make you stand out as a particularly valuable asset.

If you are an aspiring doctor, nurse, physician’s assistant, physical or occupational therapist, or even veterinary student, medical terminology is a cornerstone of your profession, and is a skill you will likely need to advance to graduate school. The good news (especially if you are a non-clinical healthcare worker) is that you do not need to attend medical or nursing school to become proficient in medical terminology.

Courses are available through many colleges and universities, often in a convenient online format. The online Medical Terminology course from the University of San Diego (USD) School of Professional and Continuing Education, for example, is a self-paced course that gives students six months to complete all units. You may also be able to find medical terminology courses through local trade schools, adult education programs, training manuals and textbooks, and even trade publications.

Proficiency in medical terminology can open up many new career possibilities — plus, it helps both clinical and non-clinical professionals become stronger members of their teams. For more convenient, practical continuing education programs, explore USD’s catalog of healthcare courses and certificates .

Where can I learn medical terminology?

Medical terminology courses are available through many colleges and universities, often in a convenient online format. You may also be able to find medical terminology courses through local trade schools, adult education programs, training manuals and textbooks, and even trade publications.

Who needs to know medical terminology?

Doctors, nurses, and other medical professionals must learn medical terminology so they can administer proper patient care and communicate with their colleagues. Additionally, many non-clinical roles are typically required (or at least strongly encouraged) to learn common terms, including healthcare informaticists, billing specialists, medical receptionists, pharmacists, medical researchers, and healthcare compliance officers.

Curriculum covered in this article

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IMPACT OF MEDICAL TERMINOLOGY ON PATIENTS' COMPREHENSION OF HEALTHCARE

Affiliation.

• 1 Kharkiv National Medical University, Ukraine.
• PMID: 30618411

Modern medical practice require close communication both doctors and patients. Development of medicine, especially seen in past decades, promoted changes in medical procedures and documentation, i.e. development of more accurate and valuable informed consent, which is an important part of treatment or diagnostic process. On the other hand, novel researches and achievements in medicine brought new terminology, descriptions and widened medical language, which complicated understanding of information both by practitioners (in any field, including psychiatry), and by patients. Clear understanding of information during diagnostic and treatment process by patients is considered an important factor of success, because researches show increasing of anxiety, depression and indifference, and decrease of involvement of patients in case of incomprehension or misunderstanding of medical information. At the same time, correct insight of information leads to improvement of patient-doctor relationships and is considered as a stimulus to reduction of morbidity and mortality and misuse of health care. Literature analysis have shown both various causes of this and ways to solve this existing problem. Most common ideas include lack of comprehension, low medical literacy and complexity of medical language. Some authors insist on existence of "medical sublanguage", due to plenty of terminology, synonymic words and constructions, which can completely replace "normal" language in some situations. Despite this development, cultural, geographical and historical influence still brings confusion in terminology. Variety of terms, which describe the same structure or process, variety of eponyms, which differ from country to county, frequently bring confusion, especially in patients, who are usually not conceived on what can the information be about. Moreover, in situation of high mobility, those geographical and cultural medical peculiarities are able to confuse even practitioners. This led to development of several classification systems and tools in attempt to equate and classify terminology.

• Communication*
• Comprehension*
• Physician-Patient Relations*
• Quality of Health Care / standards*
• Terminology as Topic*

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The Concept of Medical Terminology Essay (Critical Writing)

Introduction, medical terminology for all health care workers, the importance of medical terminology to support staff, works cited.

Medical terminology can be described as a language used by the medical professionals in the course of their work. It refers to terms used to define the human body. Medical terminology is widely used in the medical profession.

In most cases, the medical terminology uses words created using prefixes and suffixes in Latin and Ancient Greek. In medicine, the meaning and the etymology are informed of the source or the language of origin. The method is completely dissimilar to the Standard English. In this case, the root of the word can be independent in a sentence. For instance, the word nose is a word root in English that can be used without being modified (Ehrlich and Schroeder, 2).

Medical terminology is a prerequisite for all health care workers. It is the jargon of the health care industry. The health care workers need it because the appropriate or accurate terminology effects or instrument quality patient care and fewer or no errors. Health care workers should know that medical terminology is medicine’s language and prolongs care for patients.

Medical terminology makes it easier for the health care providers describe the patient’s conditions accurately. In this case, by sharing precise medical language, they can share accurate information without much wastage of time. Medical terminology is the universal language of medicine (Chabner, 45).

Thus, it facilitates the movement of patients from one medical institution to another without a lapse in care. This works efficiently when the medical information is correctly coded. The medical terminology helps the health care professionals to communicate effectively while handling patients. Medical terminology helps the health workers to understand words and their meanings hence helps them to identify locations of critical organs and functions of the body (Simmers, Simmers-Nartker and Simmers, 139).

The medical support staff includes office, clerical, and custodial staff. The support staff too requires to be conversant with the medical terminologies. In this case, without this knowledge, they may end up loosing their career. After being employed in the healthcare organizations, they are trained under medical support programs that prepare them to work in medical offices. In many cases, they collect patients’ notes and make sure that the patients’ important records go to the required or correct health care professional.

It eases their work when they use medical terminologies. For instance, one can effectively put down something before checking the spelling later. In this case, the medical terminologies become effective as a medical officer can quickly write down what is said by the patient. In this case, clerks or office administrators may write NPO instead of nothing by mouth, DX instead of diagnosis, and STD instead of sexually transmitted diseases.

Consequently, the terminology is critical in cases where patients talk a lot. Therefore, using the terminology, they are able to capture what is being said. The support staff is part of health services Frontline staff hence cannot be excluded from using the medical terminology.

Any person working in any medical field requires use medical terminology while communicating. In the medical field, there can be no excuse of not knowing medical terminologies. All people involved in the medical profession and curious patients should be conversant with the medical terminologies to be efficient. Medical terminologies clear all doubts and confusions in the medical field, which is characterized by health care providers, support staff, and patients.

Chabner, Davi-Ellen. The Language of Medicine . Saint Louis, Mo: Saunders/Elsevier, 2011. Print.

Ehrlich, Ann, and C.L. Schroeder. Medical Terminology for Health Professions . Clifton Park, NY: Delmar, Cengage Learning, 2013. Print.

Simmers, Louise, K. Simmers-Nartker, and S. Simmers-Kobelak. Diversified Health Occupations . Clifton Park, NY: Delmar Cengage Learning, 2009. Print.

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Original research article, the impact of medical terminology in self-triage decision-making.

• 1 Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, ON, Canada
• 2 Department of Medicine, McGill University, Montreal, QC, Canada
• 3 Center for Medical Education, McGill University, Montreal, QC, Canada

Objective: The present study examined whether medical terminology impacts self-triage decisions (deciding if and when to seek medical treatment) compared to lay terminology.

Methods: Undergraduate psychology student participants read 32 hypothetical health scenarios and reported how urgently they would seek care [“In this situation, when would you seek medical attention?” presented along with a seven-point scale, with anchors at either extreme: “Never (At the next scheduled appointment, if at all)” and “As soon as possible (Within the hour),” reflecting the options coded as 1 and 7, respectively]. Data were collected in person via a paper-based questionnaire. Scenarios included a description of symptoms, which were labeled as consistent with a particular medical disorder using either a lay disease label (e.g. “Heart Attack”) or medical terminology (e.g. “Myocardial Infarction”). The 32 health scenarios represented medical disorders that purposefully reflected a spectrum of severity, commonality, and how recently the medical terminology had entered common use.

Results: For disorders for which medical terminology has been more recently established, participants reported that they would seek care more urgently when the disorder was presented using a medical label [mean (SE) = 4.08 (0.23)] than when they were described using the lay disease labels [3.32 (0.23), t (35) = 5.36, p < 0.001, e.g., “seborrheic dermatitis” versus “chronic dandruff”]. However, this differential response to medical or lay disease labels was not observed for disorders for which medical terminology has been more well established [medical labels = 5.16 (0.18); lay labels = 4.89 (0.18), t (35) = −1.67, p = 0.104, e.g., “heart attack” and “myocardial infarction”].

Conclusion: These results indicate that self-triage decision-making can be readily influenced by the terminology used to identify a disorder; however, this phenomenon appears to be particularly relevant for disorders in which public opinion may still be in flux.

Medical decision-making is a very complex task ( Higgs and Jones, 2000 ; Eva, 2005 ) and even expert clinicians have difficulty with the ambiguity inherent in many clinical symptoms ( Brooks et al., 1991 , 2000 ; Zarin and Earls, 1993 ; Hatala et al., 1999 ; LeBlanc et al., 2001 , 2002 ; Groves et al., 2003 ). Issues of symptom identification and medical decision-making exist for patients as well, as we all have to decide whether something is “strange” or “bad enough” to seek medical attention, and patients often have to make health decisions without the benefit of medical expertise ( Redelmeier et al., 1993 ; MacKichan et al., 2017 ). While many treatment decisions are made through exercises in shared decision-making (where patients and physicians are both involved in treatment decisions, e.g., Charles et al., 1997 ; Frosch and Kaplan, 1999 ; Godolphin, 2009 ) or patient-centered care (where patients are at the core of medical decisions, e.g., Stewart et al., 2000 ), one example of decision-making that rests entirely with an individual is deciding when, and how urgently, to seek out medical care (previously labeled as self-triage decision-making; Cooper and Humphreys, 2008 ; Hall et al., 2010 ; Morita et al., 2017 ). To add a layer of complexity, many individuals face the difficulty of making self-triage decisions in the context of high levels of uncertainty, both in deciding whether their symptoms merit medical attention at all, and when faced with a wealth of potential diagnoses. Individual decisions are rendered even more complex and dynamic with the influence of potentially unreliable or overly fear mongering ( Gladwell, 1995 ) information from a variety of health information sources and the unfamiliar language of medical symptoms and diagnoses ( Young et al., 2008 ). Previous work has found that perceptions of the severity of disorders are influenced by the use of medical language ( Young et al., 2008 ), where conditions described using medical terminology were seen as more serious and more representative of a disease. Previous work has also found that self-triage decisions are influenced by uncertainty ( Cooper and Humphreys, 2008 ; Hall et al., 2010 ); however, we know little regarding how medical terminology and uncertainty interact in the context of self-triage decision-making. The purpose of the present study was to examine whether self-triage decisions are influenced by the terminology used to describe potential diagnoses.

Self-Triage Decision-Making

Difficulty identifying signs and symptoms for the lay individual invariably influences the amount of time before medical care is sought ( Burnett et al., 2005 ) and experimental research demonstrates that uncertainty can influence the hypothetical medical decisions of young, healthy individuals ( Cooper and Humphreys, 2008 ; Hall et al., 2010 ). These experimental investigations of decision-making suggest that factors such as certainty, severity, and the presence of alternate potential diagnoses influence the self-triage process. By manipulating the certainty [you have (diagnosis X), versus you may have (diagnosis X)] of the suggested diagnosis as well as the severity [(diagnosis X) could be a common cold or a brain aneurysm] of various hypothetical situations, Cooper and Humphreys were able to determine the role of each on the urgency with which participants report they would seek care. As one might predict, participants reported seeking care more urgently when suggested that they might have a more serious condition rather than a less serious one. Interestingly, an interaction was found between the severity of the suggested disorder and the certainty of that suggested diagnosis. Meaning, when participants were given scenarios with moderate or high severity disorders, participants responded with higher urgency ratings (on a 7-point scale) when given definitive diagnoses than when the diagnoses were suggested, and ratings of urgency were even lower when no diagnosis was provided. Conversely, with increasing certainty for low severity disorders, participants responded that they would seek care with less urgency. In summary, if it could be a serious condition (e.g. meningitis), participants reported being willing to seek treatment quickly and when it was most likely not a serious medical condition (e.g. a viral infection), they were less likely to report seeking urgent care. In addition, when given a definitive diagnosis, participants reported being willing to seek treatment more quickly than when given a suggested diagnosis that was less certain.

Hall et al. (2010) examined the influence of presenting multiple possible diagnoses on self-triage decisions. In their study, participants saw hypothetical health scenarios where a cluster of symptoms could be presented with either a high severity disorder, a low severity disorder, or with a differential diagnosis including both the high and low severity disorders. Participants rated that they would seek care more urgently for the high severity disorder (5.0 on a seven-point scale) than for the low severity disorder (3.6). More importantly, when participants saw the differential diagnosis containing both the high and the low severity disorders, they reported that they would seek care less urgently than when presented with the high severity disorder alone (4.6). These results indicate that self-triage decisions can be influenced by something as simple as the number of potential diagnoses listed or considered. In summary, previous research in this domain suggests that uncertainty plays an important role in self-triage decision-making. However, a question that remains is whether other forms of uncertainty, such as uncertainty that is induced by the use of unfamiliar terminology, also influence self-triage decision-making.

The Effects of Using Medical Terminology

In addition to the presentation of multiple possible diagnoses, many potential diagnosis and symptom labels are frequently presented to lay individuals in complex medical language—often referred to as “medicalese” ( Eva et al., 2001 ; Norman et al., 2003 ; Young et al., 2008 ). Medicalese refers to the use of specialized language to refer to medical disorders by using Latin or Greek derivatives (e.g., “Myalgic Encephalopathy”) or using English-based technical terms that connote a special medical status (e.g., “Gastroeophageal Reflux Disease”). Overall, a disease presented in medical language is typically considered to be more severe, more representative of a disease, and less prevalent ( Eva et al., 2001 ; Norman et al., 2003 ; Young et al., 2008 ). Interestingly, medical language has been demonstrated to influence the perceptions of not only lay individuals ( Young et al., 2008 ), but also early medical learners and practitioners ( Eva et al., 2001 ; Eva and Wood, 2003 ; Norman et al., 2003 ). However, some research suggests that this influence of language may be limited to newly medicalized disorders—disorders where the medical language is still quite new, and perhaps poorly recognized ( Young et al., 2008 ) and that this use of medical language may be involved in changing public perceptions of newly medicalized disorders ( Young et al., 2008 ). But perceptions of severity, disease representativeness, prevalence, and personal risk ( Young et al., 2013 ) may not be perfectly analogous to patient decisions of when to seek care (i.e. self-triage decision-making). One might think a disorder is serious and a representative example of a disease, but it may not influence how quickly one would seek medical care. Perhaps even more importantly, it is possible that the use of a medical label for a disorder may increase the urgency with which one would seek care compared to the same disorder when presented using a lay label.

The Present Study

The purpose of the present study was to investigate the role of medical and lay terminology on how urgently individuals report that they would seek care. The use of healthy undergraduates and hypothetical health scenarios to investigate the urgency to seek care has been used previously ( Cooper and Humphreys, 2008 ; Hall et al., 2010 ), and a similar population and questionnaire-based experimental approach were used here to determine the influence, if any, of medical terminology on self-triage decision-making. If this influence can be established, this will be a clear addition to previous findings indicating that medical terminology can influence perceptions of risk ( Song and Schwarz, 2009 ; Topolinski and Strack, 2010 ; Young et al., 2013 ; Dohle and Siegrist, 2014 ; Tasso et al., 2014 ), and perceptions of severity and disease status ( Young et al., 2008 ).

Participants

Thirty-six psychology undergraduate students (24 females) from McMaster University participated in exchange for partial course credit. Previous work ( Frewer et al., 2002 ) have found that perceptions of risk are more extreme in lay, older, and less educated populations, and responses are more likely to be heterogeneous within heterogeneous population. Given this study is an initial investigation into the impact of medical terminology on self-reported ratings of urgency, we opted to rely on a healthy undergraduate population in order to isolate, to the best of our ability, the influence of medical terminology on self-triage decision-making. Inclusion criteria included being of native or near-native English fluency. The study was described on the available on-line platform hosted by the Undergraduate Psychology Program at McMaster University (available to all registered students), and potential participants self-selected to participate through the on-line platform, and respondents are typically first or second year students enrolled in courses in the Psychology, Neuroscience, and Behavior Department at McMaster University. This study received approval from the McMaster University Research Ethics Board.

Participants were briefed regarding the study protocol and provided written consent. Participants completed a paper and pencil questionnaire including 32 hypothetical health scenarios (see the Appendix for examples of these scenarios). As part of the protocol, the experimenter emphasized that for each scenario, participants were to imagine that they were experiencing the given symptoms and had learned that these symptoms were consistent with a particular medical disorder. For each hypothetical scenario, participants were told to indicate, to the best of their judgment, how urgently they would seek care [on a seven-point scale anchored “Never (At the next scheduled appointment, if at all)” and “As soon as possible (Within the hour)”], a scale previously used within similar study contexts, with a similar study population by Cooper and Humphreys (2008) and Hall et al. (2010) . Participants were given an opportunity after each scenario to list any words that they did not recognize. After completing the questionnaire, participants were debriefed regarding the specific purposes of the experiment and invited to ask any questions they might have. Participants were encouraged to complete the study within 1 h, which based on previous studies ( Cooper and Humphreys, 2008 ; Young et al., 2008 ; Hall et al., 2010 ) provided ample time. Participants were responsible for self-pacing throughout the study.

Hypothetical health threat scenarios were created based on the protocol described in Cooper and Humphreys (2008) and modified to investigate the differential influence of medical and lay terminology on self-triage decisions. Disorders included in this study were purposely chosen to represent a breath of severity, commonality, and likely familiarity (specifically how long the medical language label had been in common use). Each scenario contained three to four symptoms along with a suggested diagnosis consistent with the listed symptoms. The symptoms and associated disorder were unique to each hypothetical health scenario. Each scenario ended with the question “In this situation, when would you seek medical attention?” presented along with a seven-point scale, with the following anchors at either extreme: “Never (At the next scheduled appointment, if at all)” and “As soon as possible (Within the hour),” reflecting the options coded as 1 and 7, respectively. Ratings from this seven-point scale are referred to as urgency ratings. Example scenarios are presented in the Appendix.

Four versions of the study questionnaire were created, each containing a total of 34 hypothetical health scenarios, in order to counterbalance the language of presentation (either lay or medical label for each disorder) and the order of presentation of the disorders. Sixteen of the hypothetical health scenarios in each questionnaire were related to the purpose of the present study and are described here. The remaining scenarios were part of a larger, on-going study of factors influencing self-triage decisions, and are unpublished data. To investigate the role of medical language on the reported urgency to seek care, medical and lay language stimuli from Young et al. (2008) were adapted to create hypothetical health scenarios. The medical disorders included eight disorders that were classified as “newly medicalized,” which were defined as having a medical term introduced or come to popular use within approximately the last 15 years (e.g., erectile dysfunction disorder) and eight recognized medical disorders, which were defined as having had a lay and medical term in popular use for more than 15 years (e.g., hypertension). These two types of disorders, along with their respective disorder types and labels are shown in Table 1 . Disorders were described using a medical label or a lay label (counterbalanced across participants, so no participant saw both the medical and lay label for the same disorder). Information regarding the justification and verification of these categories can be found elsewhere ( Young et al., 2008 ).

Table 1 . List of lay and medical labels used and associated category assignments.

Importantly, every questionnaire contained scenarios describing each of the eight recently medicalized disorders, and eight established disorders (total of 16 hypothetical health scenarios). For each type of disorder (recently medicalized/established) half of these scenarios in each questionnaire described the disorder using the medical label, and other half of the scenarios described the disorder using the lay label.

In order to examine the impact of medical terminology on ratings of reported urgency to seek care, an Analysis of Variance was conducted with type of disorder (recently medicalized/established) and terminology (medical/lay) as the within subjects factors of interest. Based on previous work ( Young et al., 2008 ), planned comparisons ( t -tests) were conducted for the recently medicalized and established disorders to specifically examine the influence of medical versus lay terminology.

Mean urgency ratings as a function of the type of disorder and type of language used are shown in Table 2 . Mean urgency ratings were submitted to an analysis of variance with type of disorder (recently medicalized/established), label type (medical/lay), and symptom cluster (16 clusters, one for each of the disorders listed in Table 1 ) as within subject factors. Participants reported that they would seek medical care more urgently when the disorder was described using the medical label (mean = 4.59, SE = 0.19) than when described using the lay label (mean = 4.06, SE = 0.19) [ F (1, 33) = 33.75, η p 2 = 0.51 , p < 0.001]. Participants reported that they would seek medical care more urgently for the established medical disorders (mean = 4.99, SE = 0.17) than for the recently medicalized disorders (mean = 3.65, SE = 0.22) [ F (1, 33) = 77.89, η p 2 = 0.70 , p < 0.001]. Despite a larger numerical difference between the means for the lay and medical labels in the recently medicalized disorders, the interaction between language and disorder type was only marginally significant, F (1, 33) = 2.48, η p 2 = 0.07 , p = 0.063 (one-tailed).

Table 2 . Mean urgency ratings as a function of the type of disorder and type of language used.

Although the interaction between label type and type of disorder was only marginally significant, planned t -tests were conducted to compare the effect of label type (medical/lay) on ratings of urgency separately for recently medicalized and established medical disorders, due to findings previously reported ( Young et al., 2008 ). For recently medicalized disorders, participants reported that they would seek medical care more urgently when the disorders were described with the medical labels (mean = 4.08, SE = 0.23) than when they were described using the lay disease labels (mean = 3.32, SE = 0.23), t (35) = 5.36, p < 0.001. For established medical disorders, the difference in urgency ratings did not differ across language of the disorder label [medical labels: mean = 5.16, SE = 0.18; lay labels: mean = 4.89, SE = 0.18, t (35) = −1.67, p = 0.104].

The purpose of the present study was to examine whether the use of medical labels influences health-care-seeking behavior in healthy young adults. To that end, we conducted an experimental questionnaire-based study where participants were asked to rate how urgently they would seek medical care after imagining that they were experiencing the listed cluster of symptoms and had learned that their symptoms were consistent with a provided potential diagnosis. In order to isolate the role of medical terminology on reported urgency of care-seeking behavior (or self-triage decision-making), participants were asked to report how quickly they would seek care for disorders that were labeled using either lay-language terminology (e.g., “sore throat”) or medical terminology (e.g., “pharyngitis”). Further, we investigated the magnitude of the influence of medical terminology on both well-established medical disorders (such as “hypertension”) and newly established or newly re-labeled medical disorders (such as “erectile dysfunction disorder”). In summary, the results of the present study indicate that when diseases were presented using their medical terminology label (e.g. “androgenic alopecia”), participants considered the diseases to warrant more urgent care than when the same disease was presented using a lay English label (e.g., “male pattern baldness”). Further, participants appear to demonstrate this differential weighting of medical terminology primarily for medical disorders that have been recently medicalized (e.g., “hyperhidrosis” versus “excessive sweating”). The results from this study support the notion that medical terminology influences the urgency with which individuals report that they would seek medical care.

It is important to note that the recently medicalized and the established diseases do differ in severity ( Young et al., 2008 ), making it unsurprising that participants reported that they would seek health care more urgently for diseases considered to be well established (e.g., “hypertension”) than for newly medicalized disorders (e.g., “gastroesophageal reflux disease”), and the findings of this study are consistent with previous work demonstrating that severity influences self-triage decisions ( Cooper and Humphreys, 2008 ; Hall et al., 2010 ). It is also possible that participants interpreted the urgency scale in this study inappropriately and relied on perceptions of illness base rates to ground their ratings of urgency, meaning that they may have reported that they would seek care more urgently for disorders they perceived to have higher base rates. This possibility seems unlikely, given that Young et al. (2008) have found that individuals consider the newly medicalized disorders to be more serious, more representative of a disease, and, importantly, less prevalent when presented in the medical rather than lay disease label. Young et al.’s ( Young et al., 2008 ) findings suggest that the increased likelihood to seek care for newly medicalized disorders presented with medical language labels in the present study is not due to an individual thinking that, for example, “gastroesophageal reflux disease” is more common than “chronic heartburn.” Therefore, the increased urgency with which individuals report they would seek care is unlikely to be explained by participants relying on base-rate probabilities ( Jemmott et al., 1986 ), or their personal perceptions of risk ( Coombs and Slovic, 1979 ).

In the present study, medical labels, compared to their lay English equivalent, were associated with higher urgency ratings in recently medicalized disorders, but no such pattern was seen in established disorders. This result replicates a similar pattern of results that was reported by Young et al. (2008) using different measures of the perceptions of illness severity. We propose that medical labels may induce uncertainty in lay populations; perhaps the labels sound unfamiliar, which may underlie the increased urgency ratings seen here. Song and Schwarz (2009) found that food additives were perceived as riskier when their names were harder to pronounce, an effect that was mediated by the perceived familiarity of the names. This fluency of processing acts as a heuristic cue for intuitive judgments of risk ( Schwarz et al., 2009 ). Dohle and Siegrist (2014) also found fluency of name pronunciation to influence perceptions of drug risk. Even when individuals were presented with an attribute that was easier to evaluate, like price, the name of the drug was an important criterion for most participants for evaluating side effects and willingness to purchase. It is important to recognize that this fluency effect is dependent on the context of the initial judgment. Previous studies report reverse fluency effects, where disfluency is interpreted positively, in instances where traits associated with disfluency, like unfamiliarity, were considered positive ( Pocheptsova et al., 2010 ; Galak and Nelson, 2011 ; Cho, 2015 ). Cho (2015) replicated Dohle and Siegrist’s (Dohle and Siegrist, 2014 ) findings that complex drug names were perceived as riskier, but found that the same complex drug names were also perceived as more technologically advanced. When asked to estimate the likelihood of FDA approval, individuals who had rated the drug names for advancedness perceived the complex drug names as more likely to be approved. In contrast, individuals who had rated the names for riskiness perceived complex names as less likely to be approved. The context of a judgment (e.g., advancedness versus risk) determined the direction of effect for fluency on perceptions ( Cho, 2015 ). The present study represents a situation where disfluency may be interpreted as uncertainty and associated with increased urgency to seek medical care. Considering that the effect of heuristic cues is more pronounced when individuals are under stress ( Chaiken, 1987 ) or in the presence of uncertainty ( Kahneman, 2003 ), decision-making, when ill and potentially facing uncertain medical terminology or diagnoses, can be especially prone to biases that may negatively impact individual or public health. Therefore, patient-generated data in the context of actual decisions may show an even greater effect of newly medicalized terms on care-seeking urgency; however, this was beyond the scope of this study.

The lack of differential response to lay and medical labels for disorders with well-established terminology is consistent with Dohle and Siegrist’s (Dohle and Siegrist, 2014 ) suggestion that heuristics like fluency would have a greater impact on newer drug products. This induction of uncertainty may mimic the pattern of results seen in Cooper and Humphreys (2008) , where uncertainty resulted in increased ratings of urgency for disorders that were moderate or high in severity. Interestingly, Hall et al. (2010) demonstrated that the presence of a differential diagnosis (an analog to increasing uncertainty) resulted in a paradoxical drop in ratings of self-reported care-seeking urgency. It is possible then, that the results presented here demonstrate not an uncertainty of diagnosis, but an uncertainty of what the newly medicalized terminology means. Therefore, it may be the case that with increased uncertainty regarding the meaning of a disease label, individuals are more inclined to consult someone who understands what the “jargon”—or medical terminology—means, such as a physician. Consistent with this, Rosen and Knäuper (2009) demonstrated that individuals placed in an uncertain situation regarding a fictitious sexually transmitted infection (STI) were more likely to seek additional information regarding the fictitious STI than individuals who were placed in a more certain situation regarding the same STI. Research on the health communication via medical disclosure and consent documentation also found that patients experienced less uncertainty when viewing documentation with both medical terminology and their corresponding lay terminology, than with just the medical terminology alone ( Donovan et al., 2014 ). Within the taxonomy of uncertainty in health communication established by Babrow et al. (1998) , uncertainty arises from five domains: complexity, quality of information, probability, structure of information, and lay epistemology. The uncertainty of what newly medicalized terminology may mean can be described as a lack of clarity, a sub-domain of quality of information, whereas an uncertainty of diagnosis would fall within the domain of probability—the perceived likelihood of a particular outcome or the presence of a range of possibilities ( Babrow et al., 1998 ). The source of uncertainty can influence the impact of uncertainty on decision, as demonstrated by the divergent effects of uncertainty on ratings of self-reported care-seeking urgency observed in this study and Hall et al. (2010) , and it is important to recognize the differences in the source of the uncertainty, in order to appropriately manage it ( Han et al., 2011 ).

Finally, recent research has demonstrated a strong role for the linguistic properties of product labels in decisions of risk—if a food additive ( Song and Schwarz, 2009 ) or drug ( Dohle and Siegrist, 2014 ) was difficult to pronounce, it was considered to be more risky than one that was easy to pronounce. If such simple linguistic phenomena, such as ease of pronunciation, or having English language versus Latinate-sounding terminology in medicine ( Eva et al., 2001 ; Norman et al., 2003 ; Young et al., 2008 ), can consistently influence our decisions regarding safety, severity, and care-seeking behavior, it offers caution for public communication and presentation of health information. Tasso et al. (2014) warned against the use of drug names that suggested their expected outcome because they were perceived as more effective and less risky than names that had no meaning or alluded to the target health issue. For example, participants perceived drug names like Dermosan, referring to its expected outcome of healthy (san) skin (dermo), to be more effective and less risky than names like Dermomal, referring to its target health issue of unhealthy (mal) skin (dermo). Ethical issues with regards to language choice arise when language is shown to readily bias perceptions and health behavior intention. Bokhour and Kressin (2015) expressed a similar concern toward potentially misinterpreted disorder labels, like hypertension, suggesting individual labels may carry their own semantic and cognitive biases. Despite being an established medical label for high blood pressure due to elevated arterial tension, hypertension is often misinterpreted as excessive general tension or stress. Associations between blood pressure and stress, although commonly held, remain controversial and unclear, especially with regards to the etiology and management of hypertension ( Bokhour and Kressin, 2015 ). As a result, patients may rely on psychological stress relief and discount the value of non-psychological interventions like diet, exercise, or antihypertensive medication. The presentation of this medical label, or other potentially misinterpreted labels, may influence self-triage, self-care management, and medication adherence ( Bokhour and Kressin, 2015 ). New medical labels should consider conflicting perceptions of lay labels and potential misinterpretations, as well as the implicit influence of language on perception and decision-making. Further research should investigate label-specific biases to inform appropriate language choice for health communications, as well as methods for preventing cognitive biases like fluency. Topolinski and Strack (2010) replicated Song and Schwarz’s (Song and Schwarz, 2009 ) findings of increased risk perceptions for more complex food additive names and found that a simultaneous oral sensorimotor task, like chewing, prevented this bias. Individuals who chewed on a cereal bar while reading food additive names reported similar levels of risk perception for both easy-to-pronounce names and hard-to-pronounce names. Topolinski and Strack (2010) took these findings as support for the notion that the ease of covert sensorimotor simulation drives fluency-based cognitive biases. Secondary sensorimotor tasks block these simulations, thereby reducing fluency effect. Whereas other approaches require additional post hoc processing to correct biases, the process proposed by Topolinski and Strack (2010) prevents the biases by blocking the processes responsible and is more applicable to the context of online health information seeking, where additional judgmental corrections are not convenient or readily available.

This study is not without limitations. A population of healthy undergraduates was used, and asked to imagine hypothetical medical scenarios. While this is not perfectly equivalent to individuals in crisis making decisions of when to seek care, we believe that the protocol used here, and in previous work ( Cooper and Humphreys, 2008 ; Hall et al., 2010 ), provide a well-controlled environment in which to investigate infrequent and potentially high-risk health decisions, and examine perceptions of medical conditions. Notably, these results do not perfectly generalize to a patient population, an older or less educated population ( Frewer et al., 2002 ), or individuals making health decisions on another’s behalf (e.g., parents making health decisions about their child), this remains an important direction for future research. Additionally, this study was designed as a within-subjects study, with little opportunity to investigate the role of culture (e.g., Kirmayer, 1992 ), personal experience, nor familiarity with medical terminology. This study was also unable to investigate the likely iterative and interactional effects of individuals seeking information to help support self-triage decision-making. While beyond the scope of this study, the influence of culture, individual differences, and contextual and interactive factors remain important avenues for future research. Finally, any effects of terminology need to be interpreted within a particular linguistic and cultural context, and it remains unclear the extent to which these results would generalize to languages other than English, or other cultural contexts.

Importantly, this study clearly identifies terminology as an influence on self-reported urgency to seek medical care. Understanding the specific factors that underlie the influence of medical terminology, identifying influences on patient decisions to seek care, and evaluating their interactions are important for improving medical communication generally and patient–physician communication specifically, as well as the effective design and use of public health campaigns. Physicians should consider the impact of previous exposure to lay or medical labels on patients’ sense of urgency for care and perceptions of disease characteristics ( Young et al., 2008 ), as well as the impact of their own choice of disease label during patient–physician communication. Patients reported preferring physicians’ use of medical labels because it validated their illness and enhanced their views of their physician’s professionalism ( Ogden et al., 2003 ). Consistent with findings that lay labels are perceived as less severe, less representative of disease, and more prevalent ( Young et al., 2008 ), patients also felt a physician’s use of lay labels indicated that the disease was less worrisome and would subside quickly ( Ogden et al., 2003 ). Based on this growing body of work, physicians should also avoid instances where particular labels may be misinterpreted and as a result, undermine treatment ( Bokhour and Kressin, 2015 ). The optimal terminology to be used by physicians in consultations depends on the language used by patients and the intended outcome. Williams and Ogden (2004) found increased patient–physician rapport, patient communication comfort, and patient compliance intent when physicians used the same labels as their patients.

The importance of medical terminology can also be observed outside of a physical patient–physician interaction. This study focused on the terminology seen in the context of fictional self-triage decisions, the role of uncertainty in light of different self-posited diagnoses is particularly important given our technologically and informationally rich environment, where individuals seek much of their health information online. With individuals reporting self-triage as one of the primary reasons for online health information seeking ( Bowes et al., 2012 ), decisions to seek care are now influenced by publically available information, most of which is found on the Internet ( Morahan-Martin, 2004 ). More specifically, searching for health information may actually escalate health concerns ( White and Horvitz, 2009 ; Fergus, 2013 ) and health information “facts” are often hard to find and are rarely contained within the same information site ( Benigeri and Pluye, 2003 ). Further, information on the Internet is not always reliable ( Diaz et al., 2002 ), frequently includes multiple possible diagnoses that range in severity, and diseases are often presented in technical or medical terminology (e.g. “medicalese”; Eva et al., 2001 ; Norman et al., 2003 ; Young et al., 2008 ).

With advances in information technology, the importance of terminology also extends to interactions with tools for medical decision-making ( Nijland et al., 2008 ). Decision aids, like the strategy for off-site rapid triage, a web-based decision aid designed in response to the 2009 H1N1 influenza pandemic, aim to provide better informed decision-making during times of medical crisis ( Kellermann et al., 2010 ). Dolan et al. (2015) demonstrated that user decision outcomes varied with the presentation of labels during decision aid use, suggesting that decision aids need to consider conscious and unconscious biases to be maximally effective. The present findings demonstrate that language of presentation can be a crucial consideration for patient communication, including the methods for designing decision-aid tools.

Ethics Statement

This study received approval from the McMaster University Research Ethics Board. Participants were briefed regarding the study protocol by MD and provided written consent. This study was carried out in accordance with the recommendations of the McMaster University Research Ethics Board with written informed consent from all participants. All participants gave written informed consent in accordance with the Declaration of Helsinki.

Author Contributions

MD aided in the conceptualization and execution of the study. She was primarily responsible for data analysis and partial drafting of the manuscript. She critically reviewed the manuscript and approved its final form. KH aided in the conceptualization of the study, and assisted with data analysis and interpretation. She critically revised the manuscript and approved its final form. TL assisted in data interpretation and critical revisions of the manuscript. He approved the final manuscript. MY assisted in the conceptualization of the study, assisted in data analysis and interpretation, critical review of the manuscript, and approved of its final form.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The authors would like to thank the members of the Cognitive Science Laboratory at McMaster University for their assistance throughout this project. This work was supported by Natural Sciences and Engineering Council of Canada (NSERC) grant #293145 to KH, and by a master’s and a doctoral NSERC Canada Graduate Scholarship to MD.

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Sample Scenario (Recently Medicalized Disorder)

Language labels were not presented to the participant, but are included here for illustrative purposes. Language of label used to describe the disorder (either medical or lay) was counterbalanced across participants.

Lay Label Version

Medical label version.

Keywords: decision-making, medical terminology, self-triage, urgency, medicine

Citation: D’Angelo MC, Humphreys KR, Li T and Young ME (2017) The Impact of Medical Terminology in Self-Triage Decision-Making. Front. Commun. 2:6. doi: 10.3389/fcomm.2017.00006

Received: 17 March 2017; Accepted: 04 July 2017; Published: 26 July 2017

Reviewed by:

Copyright: © 2017 D’Angelo, Humphreys, Li and Young. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Meredith E. Young, meredith.young@mcgill.ca

264 Medical Research Topics for The Proposal Of The Year

Still worried about your research?

But why? Can’t find a medical research topic?

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Your worry is here now because Christmas came early this year, and we’re pretending to be Santa with a bag of 250+ medicine research topics.

Exploring the realms of medical research within the field of medicine often presents the challenge of crafting an original and compelling topic for a research paper. When it comes to addressing how to write an 8-page paper in medical research, this task can indeed seem daunting. With so many different areas to focus on, from public care concerns to cancer treatment studies, it can be tricky to decide where your interests lie. However, we aim to help students find new research angles and focus on medical research paper topics. With our ideas coming right ahead, you can write a rigorous research paper that can win the heart of your supervisor and you can also get professional  medical paper help  for Paper Perk to ace your paper. 

Table of Contents

Medical Research Topics: Cancer, Genetics, Women’s Health, and more

Put your worries to an end as our writers have come up with a bunch of topics to help you on your quest for your medical research paper. Here are 264 medical research topics that you can choose or get your inspiration from:

Medical Research Topics for Narcotics and Addiction

• Drug addiction in students by hanging out with other people who use drugs
• Damages of starting to use drugs when young
• What are the treatments for drug addiction?
• Learning to deal with your problems so you don’t use drugs again
• Medicines that help with drugs withdrawal symptoms
• Drug addiction among mentally struggling individuals
• Treatment and rehabilitation facilities for drug addicts with mental problems
• Drug addiction and poor condition of rehabilitation facilities in developing countries
• How can drug use and addiction be prevented?
• Mental health evaluation after rehabilitation
• Coping with drug problems
• Driving under the influence of drugs: Law and Penalties
• Overdose and poisoning with heroin
• First aid in cases of drug addiction
• Drug and Alcohol Abuse Treatment
• Approach to the magnitude of the abuse/dependency problem based on the demand for care and treatment
• Identifying the attended and unattended demand related to drug use
• Drugs Addiction: Myths and Facts
• Useful in the comparison of socio-demographic profiles, consumption patterns, and types of substances among the users
• Support networks in relation to drug use
• Drugs in everyday environments
• Drugs in recreational leisure: being “partying”
• Adolescents and drugs: their relationship with delinquency
• Drug tests and approaches to improve them
• Use of drugs in minors and juveniles

Satisfied with these medical topics for research papers? If not, check out the next section where you can get new medical research topics related to cancer.

Read More:  Accounting Research Topics

Medical Research Topics About Cancer

• Why the Modern Lifestyle is to Blame for the Rise in Cancer Cases
• Awareness regarding breast cancer in women
• Awareness, causes, and treatment of Cervical Cancer
• Research proposal about ovarian cancer
• Early-stage breast cancer treatment
• Role of chlorofluorocarbons in the rising number of cancer patients
• Is it possible that electromagnetic radiation or electromagnetic waves from phones can cause cancer?
• Understanding the role of fibroblasts in improving the response to immunotherapies in lung cancer
• Study of the surface of some of the medulloblastomas
• Comorbidities and co-medications in ovarian and endometrial cancer
• Describe the behavior of anti-tumor lymphocytes to improve immunotherapies in lung cancer
• Important advances in the development of new tests for the early detection of cancer
• Putting lung cancers on a chip to test their response to immunotherapies
• Evaluating sulfasalazine for acute myeloid leukemia in elderly patients
• Predicting the response to chemotherapy in pancreatic cancers
• Fight against fibroblasts associated with resistance to immunotherapies
• Designing a new therapeutic approach to HER2+ breast cancer
• Effectively treat triple-negative breast cancers before their metastatic evolution by mobilizing the immune system
• Validate a new therapeutic target against secondary lymphedema
• Study macrophage migration in tumors
• Role of the biological clock in the progression of hepatocellular carcinoma
• Predicting the efficacy of immunotherapy in non-small cell lung cancer
• Predicting the response to the combination of radiotherapy and immunotherapy
• Targeting the cell skeleton to block tumor proliferation
• Study of the mechanisms allowing the growth of melanoma metastases
• Targeting cancer stem cells to counter radiotherapy resistance in breast cancers
• Study of tumor heterogeneity in breast cancers
• Evaluation of Tumor Heterogeneity in Parametric Imaging
• Molecular characterization of rare breast tumors
• Prevent fibrosis induced by radiotherapy

Our team’s effort in providing you with medical term paper topics is praiseworthy. You can choose any one from the list and write mesmerising details on these subjects.

Read More:  Legal Research Paper Topics

Medical History Research Topics

• Ultrasonic Research History
• History of Medical Tests with Living Beings
• History of the Development of Modern Psychiatry
• History of the Development of Osteopathic Medicine
• Medical history: content, property, and access
• From medical records to electronic health records: The course of medical history
• History of X-Ray Photography and its Efficacy in the Diagnosis of Pulmonary Disease
• Introduction to Hygiene in Medical Practice: A Revolutionary Development
• Application of Drugs of Frequent Abuse in Medical Practice
• Origin of the Clinical History
• Theory of ICT inclusion in the Public Health Administration
• Electronic Medical Records
• Psychological and social aspects of clinical history
• Evolution of the Clinical History
• Clinical history as a tool to improve the care process
• Modernization Plan in Health
• Physicians in Totalitarian Regimes, Service Assassins, or Victims of the System?

Read More:  History Research topics

Genetics Research Topics

• Source ancestral variants and mutations related to diseases
• Origin, migrations, and phylogenetic relationship of original populations, component
• Genetic Ancestry
• Nutrigenomics: identification of markers associated with nutritional problems such as obesity, malnutrition, food intolerance
• Process and origin of ames mutagenesis
• Genetic basis of adverse reactions with Pharmacovigilance Center
• Chromosomal aberrations
• Tests to determine damage to genetic material
• A historical approach using genetic markers
• Ames mutagenesis test
• Immunogenetics: Human genomic variants associated with infectious diseases and
• immune response
• Genetic anomalies and autoimmune diseases
• Genetic Response to Xenobiotics
• Chromosomal analysis
• Pharmacogenomics: variation in the metabolism of xenobiotics, including drugs
• Personalized medicine according to tumor mutation
• Genetic Analysis of  COVID-19  Specimen
• Genetic components in chronic diseases
• Rare or Orphan Genetic Diseases
• Unusual aspects of hereditary transmission
• Multifactorial (complex) inheritance
• Factors affecting gene expression
• Monogenic abnormalities
• General Review of Genetics
• New generations of sequencers
• The development of pharmacogenetic tests
• Chromosomal analysis by DNA chip
• Medical genetics: organized know-how
• Essentials of Genetics
• Regulation of the switching of fetal to adult hemoglobin
• Study of a new factor involved in the biosynthesis of the bacterial wall
• Genetic screening and functional characterization of mutations
• Physiological and genetic characterization of epilepsies: Comparison of humans and in animal models 
• Communication of genetic research results: a reflection of parents with autistic children
• Characterization of biodiversity using genetic analysis
• Biotechnology and patents: the case of pharmacogenomics
• Study and analysis of mutagens
• Ethical, social, and legal issues related to prenatal genetic tests

Read More:  Music Research Topics

Clinical Research Topics

• Medical Education
• Cooperation with patients and the public and experiential knowledge
• Subtle health approaches for people who use drugs
• Front-line clinical and organizational practices
• Prevention and management of chronic diseases
• Critical care and first-line care
• Emergency care for children and immediate help
• First aid in traffic accidents and burn victims
• Fostering community consultation and research collaboration
• Results of choosing to do an arthritis research project
• How to deal with patients from different religious and cultural backgrounds
• Clinical case and literature reviews
• Evaluation of user interfaces in mobile health applications
• Evaluation of the manufacturing process of antimicrobial removable dental prostheses 
• Evaluation of the acquisition of clinical reasoning
• Chemistry and Pharmacy Career In The United States
• Pharmacogenetics in the clinical laboratories
• Clinical supervision and coordination
• Model to estimate the demand and manage the inventory of standardized antibiotics
• Indicators for evaluating the management of special mental health care units
• Application of management control systems in Government Hospitals
• Performance measurement and proposals for improvement in private health emergency units
• Review and analysis of the requirements to register pharmaceutical products in the United States of America
• From traditional pharmaceutical marketing to digital pharmaceutical marketing in direct sales of pharmaceutical products
• Situational analysis of Herceptin Subcutaneous
• Malignant Hyperthermia
• Description of clinical records of dogs and cats with urinary tract infections
• Bone metabolism markers in gingival crevicular fluid as a potential diagnostic tool for chronic inflammatory diseases 
• Review and regularization of technical documentation of health registration of pharmaceutical products in the area of regulatory affairs
• Design of a strategy to incorporate an electronic medical record system in an oncology clinic
• Characterization of the implementation of professionalism in the form of nursing students
• Implementation of a diagnostic method for avian botulism and its application
• Behavior against leaks post sleeve gastrectomy
• Optimization of packaging processes in a pharmaceutical laboratory
• Design of management control and strategic monitoring system for a digital public hospital with concession operations

Read More:  Nursing Research Topics

Controversial Medical Research Topics

• Is It Critical to Shift Scientific Research Toward Adult Stem Cells Instead of Embryonic Stem Cells?
• Should the world Open an Organ Market?
• Should Society Turn to Alternative Medicine?
• Should Eating Disorders be considered Medical Illnesses?
• What is the New Problem Created by Electronic Cigarettes?
• How Does Stress Affect Health Development?
• What is the Role of Physical Exercises in the Prevention of Heart-Related Diseases?
• How is Formula Feeding Related to Early Childhood Obesity?
• What is the Role of the Family in the Treatment of Sleep Disorders?
• Social Factors Affecting the Development of Schizophrenia and Final Progression
• Why It’s Important to Raise Public Awareness of Bipolar Disorder
• How Breastfeeding Affects a Child’s Future Development
• Is an Anti-Tobacco Campaign Effective from a Medical Point of View?
• Why It Is Important to Involve Trained Dogs in the Treatment of Neurological Patients
• Is Being Vegetarian a Healthy Option?
• Is Prenatal Illness a Justifiable Reason for Parents and Health Care Workers to Opt for Abortion?
• Who Should Decide to Donate the Organ of a Dead Person?
• Is It Acceptable That Parents Are Allowed To Influence Their Children’s Future By Predetermining Their Hair Color Or Gender?
• Can a person be forced to donate organs under any condition?
• Where is the Line Drawn Between Social Security and the Right to Privacy?
• Can the Death Penalty be Executed Humanely?
• Is there room for Medical Errors when it comes to Euthanasia?
• Is cloning equivalent to Invading a Divine Territory?
• Is cloning a Complication or a Solution?

Read More:  Political Science Research Topics

Medical Research Topics about Diabetes

• The Growing Concern About the Increase in Cases of Insulin Resistance
• Relationship between metabolic control of patients with diabetes and work absenteeism
• Resistance in adolescents with secondary education
• Peripheral neuropathy in lower limbs in people with type 2 diabetes
• Risk factors in first-degree relatives of adults with diabetes
• The pattern of alcohol consumption in the  population with diabetes
• The participation of the family in the control of the patient with diabetes
• Research to identify how anxiety and depression affect glucose levels in some patients
• Personal factors, perceived barriers, and consultation attendance of people with type 2 diabetes
• Personal factors, social support, and lifestyle of the diabetic patient
• Muscular endurance exercise in adults with diabetes
• Maternal dependent care and self-care in a pediatric population with diabetes
• Health-promoting behaviors in adults with diabetic patients
• Dental caries and non-insulin-dependent diabetes mellitus
• Characteristics of diabetes
• Diabetic analysis according to the degree of metabolic control
• Characteristics of episodes of temporary disability in the diabetic population
• Limitations and strengths of the studies related to diabetes
• Disability episodes according to the degree of metabolic control
• Characteristics of the population of diabetic and non-diabetic women
• Diabetes and primary health care
• Approach and control of diabetes
• Diabetes and work capacity
• Glycemic control and presence of complications
• Regulation of diet for people with diabetes

Read More:  Psychology Research Paper Topics

Medical Research Topics: Infectious Diseases

• Is attention focused on death from HIV/AIDS?
• Effects of Pandemic Diseases on Human Society and the Development of Medicine
• Recurrent infections in children 
• Chronic Infectious diseases
• Information and research on  infectious diseases : Past and Present
• Future of research and remedies for infectious diseases
• Research about finding a cure for HIV
• Zika virus: Understanding the emergence and spread
• Antibiotic resistance
• People with cancer suffering from infectious diseases
• Difference between viral and bacterial infections
• Difference between infectious and contagious
• Coping with stress and anxiety caused by a diseases outbreak
• Importance of hygiene in avoiding infections
• Germs and hygiene: How to prevent infections
• Understanding germs to protect yourself from infections caused by bacteria and viruses
• Dangers of sharing items like toothbrushes, combs, and straws
• Most frequent symptoms of infectious diseases
• Difference between the virus and bacteria: A genetic analysis
• Single-celled germs that multiply rapidly
• Infection caused through direct contact with a person who is sick
• Infections caused by insect or animal bites
• Infectious diseases caused by contaminated food, water, soil, or plants
• Sexually transmitted diseases

Read More:  Research Paper Topics

Medical Research During COVID-19 Pandemic

• Anticipating the risk of importation of COVID19 according to geographical areas
• Infected patients: a study of viral kinetics in untreated patients
• Utilizing social sciences to raise awareness among the public and prepare SOPs for the threat of Coronavirus
• Exposure to the Novel 2019 Coronavirus by virological and immunological studies
• Replicating Coronavirus for the purpose of virology research
• Global joint efforts to aware the public cooperate and contribute development the vaccine
• Which vaccine is better? A research analysis of every COVID-19 Vaccine available on the market
• Molecular Virology and Immunology Unit working on Coronavirus
• Establishment of the antibody profile in convalescent patients and development of serological tests
• Coronavirus spread risk in live animal markets and endangered wildlife
• Role of fruits in the maturation of the Spike protein of SARS-CoV-2
• Adaptive multicentre study of the efficacy and safety of treatments for a hospitalized patient with a COVID 2019 infection
• Prolonged COVID-19 in an Immunocompromised Patient

Read More:  Social Work Research Topics

Mental Health Research Topics

• Psychological Consequences of Prolonged Mobile Phone Use
• Binge eating disorder: Causes, Symptoms, and Treatment
• Autism spectrum disorders
• Borderline personality disorder
• Post-traumatic stress disorder
• Obsessive-compulsive disorder: When unwanted thoughts or repetitive behaviors take over
• Disruptive Mood Dysregulation Disorder: The Basics
• Panic disorder: When fear overwhelms
• Social Anxiety Disorder: Beyond Simple Shyness
• Generalized Anxiety Disorder: When You Can’t Control Worry
• Bipolar disorder in adolescents and young adults
• Bipolar disorder
• Seasonal affective disorder: More than just the winter blues
• Take Charge of Your Mental Health: Tips for Talking with Your Health Care Provider
• Frequently asked questions about suicide: How to deal and prevent suicidal behavior
• Do genes affect our mental health? What Can They Tell Me About our Mental Health?
• Eating disorders: A problem that goes beyond food

Read More:  US History Research Topics

Topics for Women’s Health in Medical Research

• Strategies to stay a healthy woman after 50
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The percentages for all 4 categories for both severity and interference are reported in eTable 1 in Supplement 1 . Scores of the individual attributes (A, B) were combined to generate burden of individual symptoms (C) and global cumulative burden across 12 symptoms (D). eFigure 2 in Supplement 1 reports the method used to generate burden of individual symptoms and global cumulative burden across 12 symptoms.

eFigure 1. Flow Diagram Describing Patients Enrolled in Current Study

eTable 1. Prevalence of 12 Individual Symptoms by 3 Attributes

eFigure 2. Method of Generating Symptom Burden at Global and Individual Symptom Levels

eTable 2. Characteristics of Burden for Remaining Symptoms Not Included in Table 3 : Multinomial Logistic Regression Analysis

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Horan MR , Srivastava DK , Choi J, et al. Multilevel Characteristics of Cumulative Symptom Burden in Young Survivors of Childhood Cancer. JAMA Netw Open. 2024;7(5):e2410145. doi:10.1001/jamanetworkopen.2024.10145

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Multilevel Characteristics of Cumulative Symptom Burden in Young Survivors of Childhood Cancer

• 1 Department of Epidemiology and Cancer Control, St Jude Children’s Research Hospital, Memphis, Tennessee
• 2 Department of Biostatistics, St Jude Children’s Research Hospital, Memphis, Tennessee
• 3 Department of Psychology and Biobehavioral Sciences, St Jude Children’s Research Hospital, Memphis, Tennessee
• 4 Department of Oncology, St Jude Children's Research Hospital, Memphis, Tennessee
• 5 Department of Pediatrics, Stanford University School of Medicine, Stanford, California

Question   What are the prevalence and factors associated with symptom burden in young (aged 8-18 years) childhood cancer survivors?

Findings   In this cohort study of 302 young childhood cancer survivors, 38% of the survivors experienced moderate or high global cumulative symptom burden. Self-reported caregiver anxiety and neighborhood-level/census-track–based deprivation were associated with greater survivor-reported global symptom burden, while meaning and purpose was a protective factor.

Meaning   The findings of this study suggest that symptoms are prevalent years after young childhood cancer survivors’ initial cancer diagnosis, and interventions to reduce caregiver anxiety and neighborhood adversity and improve resilience may alleviate symptom burden.

Importance   Symptom burden and its characteristics among survivors of pediatric cancers aged 8 to 18 years remain understudied.

Objective   To examine the prevalence of symptom burden among young childhood cancer survivors and identify associations with sociodemographic, clinical, and psychological resilience skills, and health-related quality of life (HRQOL).

Design, Setting, and Participants   A cross-sectional analysis using data collected from November 1, 2017, to January 31, 2019, in a survivorship clinic at a US-based comprehensive cancer center was conducted. Participants included 302 dyads of children aged 8 to 18 years who survived at least 5 years beyond diagnosis and their primary caregivers. Data analysis was performed from March 13, 2023, to February 29, 2024.

Exposures   Diagnosis, caregiver-reported family conflict, self-reported caregiver anxiety, neighborhood-level social vulnerability, and survivor-reported meaning and purpose.

Main Outcomes and Measures   Novel symptom-level burden, integrating the attributes of severity and daily activity interference using the pediatric version of the Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events, global cumulative symptom burden, and HRQOL using the EuroQol-5D. Multinomial logistic regression identified characteristics associated with symptom burden; linear regression assessed symptom burden and HRQOL associations.

Results   Among 302 survivors (mean [SD] age, 14.2 [2.9] years, mean [SD] time since diagnosis, 10.9 [2.9] years; 153 [50.7%] male), 186 (62.0%) had low, 77 (25.7%) moderate, and 37 (12.3%) high global cumulative symptom burden. Greater caregiver anxiety was associated with moderate (risk ratio [RR], 1.56; 95% CI, 1.09-2.24) global symptom burden. Greater neighborhood deprivation was associated with moderate global symptom burden (RR, 4.86; 95% CI, 1.29-18.26). Survivors with greater meaning/purpose were less likely to have moderate (RR, 0.42; 95% CI, 0.29-0.61) and high (RR, 0.27; 95% CI, 0.16-0.46) global symptom burden. The burden of individual symptoms displayed similar patterns. Low (Cohen d , −0.60; 95% CI, −0.87 to −0.32) and moderate/high ( d , −0.98; 95% CI, −1.53 to −0.43) general pain, moderate/high numbness ( d , −0.99; 95% CI, −1.69 to −0.29), and moderate/high worry ( d , −0.55; 95% CI, −0.99 to −0.11) were associated with lower HRQOL.

Conclusions and Relevance   In this cross-sectional study of young childhood cancer survivors, symptom burden was prevalent. Caregiver anxiety and disparity-related neighborhood factors were associated with greater symptom burden, whereas meaning and purpose was a protective factor. Greater specific symptom burden contributed to poorer HRQOL. The findings suggest that interventions targeting resilience and neighborhood adversity may alleviate symptom burden and improve HRQOL.

Pediatric cancer survivors often report various symptoms associated with treatment modalities or late effects, negatively impacting their health-related quality of life (HRQOL). 1 , 2 However, existing patient-reported outcomes (PROs) research in pediatric cancer survivorship primarily targets adult survivors and neglects children and adolescents 5 years post diagnosis and younger than age 18 years. 3

For pediatric cancer populations, symptoms can be assessed using the pediatric version of the Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (Ped-PRO-CTCAE) 4 - 7 to evaluate 3 attributes (frequency, severity, and interference with daily activities) for individual symptoms, resulting in 3 scores for each symptom. 8 The Ped-PRO-CTCAE was initially developed to assess symptomatic adverse events (AEs) in patients with cancer undergoing therapies. This study applied the Ped-PRO-CTCAE to young cancer survivors to explore residual symptomatic AEs from cancer therapies and/or emerging treatment-induced symptomatic AEs after therapy completion (ie, late effects).

While a granular view of symptom attributes is valuable (eg, gaining insight into a patient’s pain severity), there are some instances where a global symptom burden metric is clinically useful (eg, treatment decision-making for a patient with high severity but low interference of pain). To our knowledge, characteristics of symptom burden, particularly contextual factors (eg, family dynamics, neighborhood environment), have not been examined in cancer survivors who are still children (aged 8-18 years). Previous studies using the Pediatric Quality of Life Cancer Module 9 and the PediQUEST Memorial Symptom Assessment Scale 10 have identified some protective factors (eg, resilience) associated with symptomatic AEs among children with cancer undergoing therapies, but efforts to identify protective factors for symptoms are presently lacking for young cancer survivors.

This study reports the prevalence of symptom severity and interference self-reported by young childhood cancer survivors using the Ped-PRO-CTCAE. Global cumulative and individual symptom burden metrics were developed by integrating symptom severity and interference attributes. Diverse characteristics, encompassing survivor’s personal and contextual factors, were considered in associations with symptom burden. Subsequently, the association between symptom burden and HRQOL was analyzed. We hypothesized that caregiver factors (eg, anxiety), neighborhood deprivation, and survivors’ meaning/purpose may be associated with cumulative burden across symptoms. Additionally, greater burden for some symptoms (eg, worry, fatigue) may be associated with poorer HRQOL.

Participants were 302 dyads of 5-year childhood cancer survivors who were previously treated at St Jude Children’s Research Hospital, enrolled in the St Jude Lifetime Cohort Study 11 and aged 8 to 18 years at the time of assessment, and their primary caregivers (eFigure 1 in Supplement 1 provides the flow diagram). All eligible participants were approached and recruited during regular follow-ups in the hospital between November 1, 2017, and January 31, 2019. This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline. Self-reported paper-and-pencil surveys were administered to survivors and caregivers at St Jude’s survivorship clinic. Survivors self-reported their symptoms, HRQOL, and meaning/purpose; caregivers self-reported their anxiety, family conflict, and survivors’ and caregivers’ sociodemographic information. The study protocol was approved by St Jude’s Institutional Review Board; all participants provided written informed consent before data collection. Participants did not receive financial compensation for their participation in this ancillary study to the St Jude Lifetime Cohort Study.

Using the 15-item core version of the Ped-PRO-CTCAE, 12 symptoms (stomach pain, constipation, mouth pain, nausea, fatigue, general pain, headache, numbness, worry, sadness, difficulty sleeping, and cough) containing the attributes of frequency, severity, and interference were used. 6 , 7 Severity and interference attributes, more than frequency, were considered clinically meaningful and actionable. With comparable rates between severity and frequency attributes (eTable 1 in Supplement 1 ), we assessed the burden at the global and individual symptom levels using the combined severity and interference attributes of 12 symptoms. Each attribute was rated on a 4-point scale. To assess the burden of each symptom, responses were categorized as none if the survivor indicated that they did not have any severity or interference for that symptom (severity = 0 and interference = 0), low if their symptom was a little bad or the symptom had some interference (severity = 1 or interference = 1), or moderate/high if the symptom was bad or very bad or the symptom had a lot or a whole lot of interference (severity = 2 or 3 or interference = 2 or 3). To assess the global cumulative burden across 12 symptoms, the severity of each symptom was considered prevalent if the survivor reported at least a little severity (severity ≥1), and the number of symptoms with prevalent severity was counted to obtain a cumulative symptom severity score (0-12). The same dichotomization and count method was used for each symptom’s interference attribute. Following a review of item distributions and consensus among PRO methodologists (M.R.H., I.-C.H.), oncologists (G.T.A., M.M.H.), psychologists, a palliative care clinician (J.N.B.), and a statistician (D.K.S.), global cumulative burden was categorized as low if the survivor had 4 or fewer symptoms with prevalent severity and interference, moderate if 5 to 8 symptoms had either prevalent severity or interference, and high if 9 to 12 symptoms had either prevalent severity or interference, acknowledging the absence of a definitive high standard (eFigure 2 in Supplement 1 for scoring system).

Utility-based HRQOL was assessed with the EuroQol-5D Youth Report (EQ-5D-Y). 12 The EQ-5D-Y is a measure of overall HRQOL that incorporates the general population’s preferences for health states into weights for individual EQ-5D-Y items. This measure encompasses 5 dimensions: mobility, taking care of oneself, doing usual activities, having pain or discomfort, and feeling worried, sad, or unhappy. The responses to 5 dimensions were weighted according to caregiver preferences gathered from a previous validation study and combined to calculate a HRQOL score (higher for better HRQOL). 13

Clinical information, including cancer diagnosis and time since diagnosis, was extracted from medical records. Survivorship clinicians assessed study participants for chronic health conditions (CHCs), graded as 1 (asymptomatic/mild), 2 (moderate), 3 (severe/disabling), or 4 (life-threatening) using a modified version of the Common Terminology Criteria for Adverse Events (CTCAE) grades. 14 Individual CHCs were grouped by organ system, and each CHC group was assigned a composite grade based on the highest graded individual CHC within that organ system. Cardiovascular, endocrine, hematologic, and neurologic CHC groups were included in the multivariable analysis given their prevalence (n >30) and associations with global symptom burden in bivariate analysis ( P  < .20). Caregivers reported sociodemographic information, including survivors’ age at assessment (continuous in years), sex (male/female), race (American Indian, Asian, Black, White, more than 1, or unknown), ethnicity (Hispanic/non-Hispanic), primary caregivers’ age (continuous in years), mother’s educational level (below high school, high school graduate or General Educational Development, some college, college graduate, or post graduate), insurance status (private, public, or uninsured), annual household income (≤$19 999, $20 000-$54 999, or ≥$55 000), and residential address. Race and ethnicity were collected as part of the standard sociodemographic variables included in the St Jude Lifetime Cohort Study to examine the demographic variation in participants, but these variables were not included as covariates in the multivariable models.

Caregivers completed the 9-item family conflict domain of the Family Environment Scale. 15 Raw sum scores were converted to T scores with a mean (SD) of 50 (10). Scores were converted to a z score (higher for greater conflict).

Census tract–based Social Vulnerability Index (SVI) measured neighborhood adversity per the survivor’s residential address. 16 We used the overall SVI score, which encompasses neighborhood adversity across socioeconomic status, household composition, racial and ethnic minority status and language, and housing and transportation domains. Scores were dichotomized to compare survivors living in high deprivation areas (≥90th percentile of the SVI) with those living in low deprivation areas (<90th percentile of the SVI).

Caregiver’s anxiety was self-reported using the 6-item PROMIS Anxiety Short-Form 17 to capture feelings of unease, fear, and worry. Raw sum scores were converted to T scores with a mean (SD) of 50 (10). 18 Scores were converted to a z score (higher for greater anxiety).

Survivors completed the PROMIS Meaning and Purpose scale to assess feelings of hopefulness, optimism, and sense of life purpose. 19 Raw sum scores were converted to T scores. 18 Scores were converted to a z score (higher for more meaning/purpose).

Data analysis was conducted from March 13, 2023, to February 29, 2024. Descriptive statistics included frequency distributions of categorical variables and means (SDs) of continuous variables. The amount of missing data for all variables was below 10%, so available data analysis was used in all analyses. Two multinomial logistic regression models analyzed characteristics of global cumulative symptom burden and burden of each symptom. Model 1 included personal risk factors (eg, survivor’s age and diagnosis) 20 , 21 and contextual risk factors (ie, family conflict, neighborhood deprivation, and caregiver anxiety) of greater symptom burden. Model 2 added survivor’s meaning/purpose to the risk factors in model 1. For each model, low symptom burden is the reference group. Multivariable linear regression with robust SEs, as recommended by EQ-5D-Y developers, 22 , 23 assessed associations between symptom burden and HRQOL. LASSO methods were used to select individual symptoms for testing associations with HRQOL, while personal, contextual, and meaning/purpose factors were forced to stay in the model. Regression coefficients are presented as effect sizes (Cohen d ), with 0.2 to 0.49 indicating small effects; moderate, 0.5 to 0.79; and large, greater than or equal to 0.8. 24 A 2-sided P value <.05 indicated statistical significance. All analyses were performed in Stata, version 18.0 (StataCorp LLC). 25

The mean (SD) age of the survivors was 14.2 (2.9) years at the time of assessment and 10.9 (2.9) years since diagnosis; 149 (49.3%) were female and 153 (50.7%) were male; 3 (1.0%) were American Indian, 1 (0.3%) was Asian, 56 (18.5%) were Black, and 232 (76.8%) were White; 143 (47.3%) were diagnosed with solid tumors, 109 (36.1%) with hematologic cancer, and 41 (13.6%) with central nervous system tumors. Table 1 displays the characteristics of 302 survivors and their caregivers.

The Figure depicts the prevalence of severity and interference separately by 12 symptoms, the burden for each symptom combining severity and interference attributes, and the global cumulative burden across 12 symptoms. Regarding severity, the most prevalent symptoms were feeling tired (45.2%), headaches (43.6%), and difficulty sleeping (42.2%). For interference, the most prevalent symptoms were feeling tired (32.0%), headaches (27.2%), and difficulty sleeping (27.3%) (eTable 1 in Supplement 1 reports on 3 attributes of 12 symptoms). The prevalence of low global cumulative symptom burden across 12 symptoms was 62.0% (n = 186); moderate, 25.7% (n = 77); and high, 12.3% (n = 37) ( Figure ).

Having neurologic CHCs was associated with moderate (RR, 3.45; 95% CI, 1.56-7.59) and high (RR, 6.70; 95% CI, 2.36-19.07) global cumulative symptom burden for models with and without meaning/purpose ( Table 2 ; model 2 results are reported throughout this section unless otherwise indicated). Having hematologic CHCs was associated with high global symptom burden (RR, 6.17; 95% CI, 1.95-19.52). Greater caregiver anxiety was associated with moderate (RR, 1.56; 95% CI, 1.09-2.24) global symptom burden. Greater neighborhood deprivation was associated with moderate global symptom burden (RR, 4.86; 95% CI, 1.29-18.26). Survivors with greater meaning/purpose were less likely to have moderate (RR, 0.42; 95% CI, 0.29-0.61) and high (RR, 0.27; 95% CI, 0.16-0.46) global symptom burden.

Table 3 presents the results of burden for 4 symptoms of interest (feeling tired, problems sleeping, worried/nervous, and general pain) selected to balance physical, psychological, and somatic symptoms. Having cardiovascular CHCs was associated with low burden of problems sleeping (RR, 2.07; 95% CI, 1.07-3.98). Having hematologic CHCs was also associated with moderate/high burden of feeling tired (RR, 5.34; 95% CI, 1.63-17.46) and worry (RR, 4.08; 95% CI, 1.07-15.52); having neurologic CHCs was associated with moderate/high symptom burden for all symptoms except stomach pain and constipation (eTable 2 in Supplement 1 for symptoms not reported in Table 3 ). Greater caregiver anxiety was associated with low burden for problems sleeping (RR, 1.58; 95% CI, 1.13-2.20). Greater neighborhood deprivation was associated with low worry (RR, 4.30; 95% CI, 1.32-14.04). More family conflict was associated with low problems sleeping (RR, 1.55; 95% CI, 1.13-2.13). Survivors with greater meaning/purpose were less likely to report low or moderate or high symptom burden for these 4 symptoms.

At the global cumulative symptom burden level, survivors having moderate ( d , −0.72; 95% CI, −1.00 to −0.44) or high ( d , −1.37; 95% CI, −1.77 to −0.96) global burden were less likely to report higher HRQOL. To examine this association at the symptom level, 10 individual symptoms were selected into the model through LASSO methods ( Table 4 ). Low ( d , −0.60; 95% CI, −0.87 to −0.32) and moderate/high ( d , −0.98; 95% CI, −1.53 to −0.43) general pain was associated with lower HRQOL by medium and large effects. Having moderate/high numbness ( d , −0.99; 95% CI, −1.69 to −0.29) and moderate/high constipation ( d , −0.71; 95% CI, −1.41 to −0.02) were associated with lower HRQOL by large and medium effects. Having moderate/high worry ( d , −0.55; 95% CI, −0.99 to −0.11) and moderate/high sadness ( d , −0.59; 95% CI, −1.11 to −0.06) were associated with lower HRQOL by medium effects.

Approximately 40% of young childhood cancer survivors had moderate or high global symptom burdens that were evident years beyond their initial cancer diagnosis. Greater caregiver anxiety and neighborhood deprivation were linked to greater symptom burden, suggesting that caregiver’s mental health and the context where survivors live may be critical to consider in their symptom management. Survivors’ perception of life’s meaning/purpose was associated with higher symptom burden both globally and for most symptoms.

Compared with a previous report that evaluated young patients 4 to 14 days after beginning a round of treatment for childhood leukemia and lymphoma, 26 young survivors in this study reported lower prevalence for some symptoms (eg, constipation, mouth pain, and nausea). However, other symptoms (eg, headaches, worry) had a similar prevalence among patients and survivors. This finding suggests that symptoms may persist or newly emerge after therapy completion. We also found the prevalence of some CHCs was associated with increased symptom burden across different domains, suggesting the importance of early identification and intervention on CHCs to address symptom burden and improve HRQOL.

The incorporation of both severity and interference data into a single metric represents a new approach to understanding survivors’ symptom burden. While severity and interference attributes provide unique insights into individual symptoms of survivors, assessing these attributes separately provides a large volume of data that could overwhelm clinical decision-making. Cumulative burden metrics have served as the primary end point in randomized clinical trials involving adult-onset cancers for comparative effectiveness and cost-effectiveness analyses. 27 , 28 Our suggested approach, which involves integrating severity and interference attributes, is applicable in scenarios in which interpreting a single score is advantageous (eg, clinical decision-making, policy decisions). The gain in interpretability with this new approach likely comes with a loss of information and statistical power, so the method of scoring the Ped-PRO-CTCAE must be chosen with these considerations in mind.

In one study of a small sample of young childhood acute lymphoblastic leukemia survivors, risk factors associated with symptom prevalence included lower maternal educational level and family cohesion and higher parental emotional distress and parental protective behavior. 29 Our study, containing broader pediatric cancer diagnoses, also found caregiver anxiety and family conflict to be associated with moderate or high symptom burden for some symptoms more than cancer diagnosis or personal demographic characteristics. Caregivers of children with cancer have been reported to be more overprotective 30 and experience elevated distress and anxiety 31 than the general population. Using family-centered psychosocial interventions (eg, the Surviving Cancer Competently Intervention Program 32 ) may reduce survivors’ symptom burden by addressing caregivers’ anxiety, distress, and family strain and, conversely, treating survivors’ symptoms may alleviate caregivers’ anxiety.

This study revealed that neighborhood social vulnerability was associated with symptom burden. This finding is of great importance for survivors because a disadvantaged social environment, characterized by factors such as low socioeconomic status, unstable housing, and transportation barriers, can affect survivors’ physical and psychological stress and biomarkers of oxidative stress inflammation. 33 , 34 Survivors’ stress physiologic status impacts their disease trajectory from diagnosis into survivorship and is linked to poorer outcomes, such as graft-vs-host disease, disability, and cancer-related mortality. 35 Unlike patients undergoing therapy who are tethered to the hospital, long-term survivors are closely tied to their community environment, rendering neighborhood adversity a major risk factor of symptom burden.

Greater meaning/purpose was associated with lower symptom burden both at the global and individual symptom levels. Finding meaning/purpose can be an indicator of psychological resilience. 36 , 37 Survivors with resilience skills may experience the same symptoms but report less burden compared with survivors without resilience skills. It is common practice in survivorship care to address the negative risk factors of experienced symptoms, but positive psychological factors may not be as frequently emphasized. Finding meaning/purpose is a skill that can be taught and incorporated into interventions to promote resilience. Given the associations of resilience with other outcomes, including mortality, 38 future studies may offer useful interventions (eg, Promoting Resilience In Stress Management intervention for patients with cancer 39 ) to promote a mindset of resiliency to lessen symptom burden.

The coefficients for caregiver anxiety and family conflict were reduced after meaning/purpose was adjusted, suggesting that meaning/purpose is protective in the association between caregiver anxiety and family strain and higher global symptom burden. However, the associations of neighborhood adversity with symptom burden were strengthened after adjusting for meaning/purpose. Meaning/purpose is a personal-level characteristic that may impact personal and family adversity, but community-level factors, such as community cohesion, may positively affect neighborhood adversity 40 more than personal-level positive factors.

Symptom burden was associated with poorer HRQOL. The EQ-5D-Y assesses HRQOL, concentrating on symptoms and functionality, 12 unlike measures of life satisfaction or overall well-being that gauge overall life experiences. 41 Thus, it is more attuned to health issues, such as symptom burden, rather than neighborhood/family and meaning/purpose factors associated with subjective well-being. We suggest incorporating symptom screening into routine survivorship care, followed by interventions targeting specific symptoms (eg, behavioral and nonpharmacologic interventions for pain 42 ) to improve the HRQOL of young cancer survivors.

This study has some limitations. First, with a cross-sectional design, it is not possible to detect causal outcomes among risk factors, symptom burden, and HRQOL. Future longitudinal studies are needed to elucidate the temporal nature of these associations. Second, the generalizability of this study to other young survivors is limited because survivors were recruited from a single institution that specifically cares for pediatric patients with cancer and survivors. Third, the current Ped-PRO-CTCAE, which includes assessments more salient to the acute phase of treatment (eg, constipation, nausea), may not fully characterize symptomatic issues of young survivors many years after completion of therapy. Designing a survivor-specific Ped-PRO-CTCAE that includes unique symptoms experienced by young, long-term survivors of childhood cancer is needed.

In this cross-sectional study of childhood cancer survivors aged 8 to 18 years, survivors experienced symptom burden at the global and individual symptom levels. Survivors embracing a life filled with meaning/purpose have a lower prevalence of moderate or high symptom burden. Interventions targeting specific symptoms, family dynamics, and positive psychology to promote resilience, and offering resources to cope with challenging physical environments in their neighborhoods could alleviate symptom burden and enhance HRQOL for young, long-term cancer survivors.

Accepted for Publication: March 7, 2024.

Published: May 7, 2024. doi:10.1001/jamanetworkopen.2024.10145

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Horan MR et al. JAMA Network Open .

Corresponding Author: I-Chan Huang, PhD, Department of Epidemiology & Cancer Control, St Jude Children’s Research Hospital, 262 Danny Thomas Pl, MS735, Memphis, TN 38105 ( [email protected] ).

Author Contributions: Drs Huang and Horan had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Horan, Srivastava, Armstrong, Hudson, Huang.

Acquisition, analysis, or interpretation of data: Horan, Srivastava, Choi, Krull, Ness, Hudson, Baker, Huang.

Drafting of the manuscript: Horan, Srivastava, Huang.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Horan, Srivastava, Huang.

Obtained funding: Ness, Huang.

Administrative, technical, or material support: Ness, Hudson, Huang.

Supervision: Armstrong, Baker, Huang.

Conflict of Interest Disclosures: Dr Krull reported receiving grants from the National Cancer Institute during the conduct of the study. Dr Armstrong reported receiving grants from the National Institutes of Health (NIH) during the conduct of the study. Dr Ness reported receiving grants from the NIH during the conduct of the study. No other disclosures were reported.

Funding/Support: The research reported in this manuscript was supported by the US National Cancer Institute under award numbers U01CA195547, R01CA238368, T32CA225590, and P30CA021765.

Role of the Funder/Sponsor: The funding organization had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies.

Data Sharing Statement: See Supplement 2 .

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This paper is in the following e-collection/theme issue:

Published on 8.5.2024 in Vol 26 (2024)

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Authors of this article:

Original Paper

• Christian Wolff 1 , MSc   ; 
• Patrick Steinheimer 2 , MSc   ; 
• Elke Warmerdam 3 , MSc, PhD   ; 
• Tim Dahmen 1 , MSc, PhD   ; 
• Philipp Slusallek 1 , MSc, PhD   ; 
• Christian Schlinkmann 1 , MSc   ; 
• Fei Chen 1 , MSc   ; 
• Marcel Orth 2 , MD, PhD   ; 
• Tim Pohlemann 2 , MD, PhD   ; 
• Bergita Ganse 2, 3 , MD, PhD  

1 German Research Center for Artificial Intelligence (DFKI), Saarbrücken, Germany

2 Department of Trauma, Hand and Reconstructive Surgery, Departments and Institutes of Surgery, Saarland University, Homburg/Saar, Germany

3 Innovative Implant Development (Fracture Healing), Departments and Institutes of Surgery, Saarland University, Homburg/Saar, Germany

Corresponding Author:

Bergita Ganse, MD, PhD

Innovative Implant Development (Fracture Healing)

Departments and Institutes of Surgery

Saarland University

Kirrberger Straße 1

Building 57

Homburg/Saar, 66421

Phone: 49 684116 ext 31570

Email: [email protected]

Background: Monitoring of gait patterns by insoles is popular to study behavior and activity in the daily life of people and throughout the rehabilitation process of patients. Live data analyses may improve personalized prevention and treatment regimens, as well as rehabilitation. The M-shaped plantar pressure curve during the stance phase is mainly defined by the loading and unloading slope, 2 maxima, 1 minimum, as well as the force during defined periods. When monitoring gait continuously, walking uphill or downhill could affect this curve in characteristic ways.

Objective: For walking on a slope, typical changes in the stance phase curve measured by insoles were hypothesized.

Methods: In total, 40 healthy participants of both sexes were fitted with individually calibrated insoles with 16 pressure sensors each and a recording frequency of 100 Hz. Participants walked on a treadmill at 4 km/h for 1 minute in each of the following slopes: −20%, −15%, −10%, −5%, 0%, 5%, 10%, 15%, and 20%. Raw data were exported for analyses. A custom-developed data platform was used for data processing and parameter calculation, including step detection, data transformation, and normalization for time by natural cubic spline interpolation and force (proportion of body weight). To identify the time-axis positions of the desired maxima and minimum among the available extremum candidates in each step, a Gaussian filter was applied (σ=3, kernel size 7). Inconclusive extremum candidates were further processed by screening for time plausibility, maximum or minimum pool filtering, and monotony. Several parameters that describe the curve trajectory were computed for each step. The normal distribution of data was tested by the Kolmogorov-Smirnov and Shapiro-Wilk tests.

Results: Data were normally distributed. An analysis of variance with the gait parameters as dependent and slope as independent variables revealed significant changes related to the slope for the following parameters of the stance phase curve: the mean force during loading and unloading, the 2 maxima and the minimum, as well as the loading and unloading slope (all P <.001). A simultaneous increase in the loading slope, the first maximum and the mean loading force combined with a decrease in the mean unloading force, the second maximum, and the unloading slope is characteristic for downhill walking. The opposite represents uphill walking. The minimum had its peak at horizontal walking and values dropped when walking uphill and downhill alike. It is therefore not a suitable parameter to distinguish between uphill and downhill walking.

Conclusions: While patient-related factors, such as anthropometrics, injury, or disease shape the stance phase curve on a longer-term scale, walking on slopes leads to temporary and characteristic short-term changes in the curve trajectory.

Introduction

Long-term monitoring of gait patterns and plantar-pressure distributions via insoles are increasingly popular ways to study behavior and activity in the field and in the everyday lives of people and patients, including healing, personalized prevention, and treatment or disease progression [ 1 - 3 ]. In recent years, the usability of instrumented insoles for gait analyses has increased. Several technical issues could be resolved, including calibration, hysteresis and drift, durability, usability, limited energy supply and battery life, data storage capacity, and the restriction to low sample frequencies associated with higher error rates, that is, when force peaks are missed [ 3 - 5 ]. The usability of instrumented insoles is currently still limited by difficulties in data analysis. Advanced algorithms and tools are needed and currently developed to be able to draw meaningful conclusions from such insole gait data [ 6 , 7 ]. When analyzing long-term field data and developing smart health care innovations, automated data annotation is desirable to determine and quantify the activities a person has conducted. Ideally, the activity type can be determined algorithmically from the plantar pressure data alone.

Characteristic gait changes have been reported for walking on slopes, such as changes in the contribution of the ankle joint to leg work [ 8 ]. In addition, uphill walking on a treadmill increases hip and knee flexion angles during the stance phase, as well as the forward tilt of the thorax [ 9 ]. Furthermore, a decrease in dorsiflexion was observed during downhill walking at initial contact, in midstance, and during the second half of the swing phase [ 9 ]. During uphill walking with increasing inclination, more positive joint work was identified for the ankle and hip joint, while negative joint work increased during downhill walking [ 10 ]. Older individuals were shown to have a disproportionate recruitment of hip muscles and smaller increases in activity of the medial gastrocnemius muscle with steeper uphill slopes than younger adults, resulting in difficulty walking on steep slopes [ 11 ].

The M-shaped curve of ground reaction forces or plantar pressure during the stance phase is mainly defined by the loading and unloading slope, 2 maxima, 1 minimum, as well as the force during defined periods [ 12 ]. When monitoring gait continuously via insoles, walking uphill or downhill on a slope could affect the gait cycle curve in characteristic ways. If these typical changes were known, one could correct for such confounders when analyzing insole data. We hypothesized that walking on a slope generates typical changes in the plantar pressure stance phase curve that vary between uphill and downhill walking.

Study Design

This study is part of the project Smart Implants 2.0—Weight-bearing and Gait Observation for Early Monitoring of Fracture Healing and Individualized Therapy after Trauma, funded by the Werner Siemens Foundation. It was registered in the German Clinical Trials Register (DRKS00025108).

Ethical Considerations

Ethical approval was obtained from the Institutional Review Board of Saarland Medical Board (Ärztekammer des Saarlandes, 30/21).

Data Collection

Inclusion criteria were the ability to walk on a treadmill, and aged 18 years and older. Exclusion criteria were aged under 18 years, use of walking aids, inability to give consent, pregnancy, immobility, and previous injury of the lower legs or pelvis. The aim was to collect data from healthy volunteers.

The healthy participants of both sexes (none of them identified as diverse) were fitted with individually calibrated OpenGO insoles (Moticon GmbH) with 16 pressure sensors in each insole to be used in regular running shoes. Calibration to the individual body weight was conducted using the Moticon OpenGO app by letting the participants walk and shift their body weight in a standardized way. The insole size was selected to fit the individual participant’s shoe size. Measurements were conducted with a recording frequency of 100 Hz in the record mode of the device. Raw data were exported for analyses. The participants walked on a treadmill at 4 km/h (Mercury, HP Cosmos) for 1 minute while insole data were collected with 3-minute breaks for recovery. Recordings were obtained for slopes of −20%, −15%, −10%, −5%, 0%, 5%, 10%, 15%, and 20%. The participants were asked to walk for 1 minute straight, and recording was only commenced when the walking was already in progress to avoid bias by including altered steps upon gait initiation.

Data Processing

The pressure readings of the force sensors in the insole device yield a weighted sum as a total vertical ground reaction force reading. To compute the force, every summand is weighted by its sensor area and a respective scaling factor accounting for the sensor’s surrounding area, as well as gaps between sensors that depend on the insole size. This process is conducted by the Moticon software as an automated processing step before file export. Insole data were exported as described previously [ 13 , 14 ]. A custom-developed data platform was then used for further processing and parameter calculation, in which step detection was conducted as follows. The stance phases were identified and extracted from the time series data by considering any activity with consecutive force readings above 30 N. A tolerance of up to 3 missing values was implemented to account for possible recording issues. Any activity with a duration of less than 300 milliseconds or more than 2000 milliseconds was discarded. Both the force and time axes were normalized. Force readings were transformed from Newton to a proportion of the body weight of the respective participant. Of note, as plantar pressure was measured instead of weight, due to acceleration, values regularly exceeded the body weight for peak load-bearing instances. Normalizing the time axis was more complex, as the lack of a fixed cadence resulted in varying step lengths and thus differing numbers of true measurement points for each step. Therefore, a natural cubic spline interpolation was conducted on the original raw data. Based on the resulting curve for each stance phase, 100 equidistant samples were taken, resulting in an interpolated force measurement point for every 1% of the overall stance phase length. This approach accounted for the lower recording frequency and higher sensor noise inherent to the insoles when compared with other gait measuring devices, such as sensor-equipped treadmills or force plates. Parameters that describe the trajectory of the stance phase curve are usually based on or derived from the characteristic local extrema, that is, the first and second force peak and the local minimum in-between force peaks. These maxima and the minimum are used as parameters themselves to describe the curve trajectory [ 13 ]. Sensor jitter may lead to the existence of multiple ambiguous candidates for the named extrema. As a solution to this, a Gaussian filter was applied to the original raw data in a repetition of the normalization process. The applied filtering strategy (σ=3, kernel size 7) was chosen to prioritize the elimination of extrema ambiguity at the expense of signal precision. This can result in overcorrection in areas with higher signal volatility, mostly at the start and end of the stance phase. Hence, to avoid loss of high-frequency detail, the filtered and normalized curve was not used for parameter analysis, but only to determine unambiguous time-axis positions (indices) for the extremum candidates. These indices were then reapplied to the nonfiltered, normalized data to identify the corresponding plantar pressure measurement closest to the original raw data. In case the use of the filtered data still led to inconclusive extremum candidates, the following additional detection strategies were applied in the named order: (1) time plausibility: extremum candidates occurring within the first or last 10 indices (first/last 10% of overall time span) were eliminated; (2) maximum or minimum-pool filtering: should multiple extremum candidates occur within a pool size of 5 indices (equals to 5% of overall time span), the candidate with the highest or lowest force value was chosen; (3) monotony-check: in case of multiple remaining extremum candidates, candidates where the curve did not display a strict monotonous decrease or increase in both directions within 5 indices each were eliminated; and (4) monotony grace: in case the monotony check had eliminated too many candidates (less than 2 maximum candidates or less than 1 minimum candidate remaining), the eliminated candidates were reinstated in descending order of their highest achieved monotony distance until the target number of candidates was reached.

After applying these strategies, every stance activity that remained with an irregular amount of unambiguous extremum candidates was removed from the data set. In total, 585 load-bearing events were excluded as not fitting the strict parameter definitions.

For each participant, across the minute of walking all stance phase curves were extracted. The parameters illustrated in Figure 1 were calculated for each stance phase and used to analyze changes in the trajectory of the stance phase curve. To do so, data from both feet were pooled. The curve is mainly described by 2 maxima and a minimum in between the maxima, Fz2 (the first maximum), Fz3 (the minimum), and Fz4 (the second maximum). The mean force over the entire stance phase is referred to as Fmean stance . The mean force between the start of the loading phase and Fz2 is Fmean load . The mean force between Fz2 and Fz4 is Fmean mid . The mean force between Fz4 and the end of the unloading phase is Fmean unload . All these parameters have the unit percent body weight. In addition, the loading and unloading slope have the units percent body weight or percent stance phase duration. The loading slope was computed as the slope of the line defined by the start of the loading phase and the first force reading equal to or higher than 80% of Fz2. The unloading slope was calculated as the slope of the line defined by the first force reading in the unloading phase below 80% of Fz4 and the end of the stance phase event.

Statistical Analyses

Statistical tests were executed with SPSS Statistics (version 29; IBM Corp). Significance was defined as P <.05. The normal distribution of data was tested by the Kolmogorov-Smirnov and Shapiro-Wilk tests. A linear regression analysis of variance was conducted for each of the gait parameters as the dependent variable, with the slope (−20% to 20%) as the independent variable. Mean values and SD are reported. Linear regression slopes are reported for comparability and to allow for correction, even though for some of the parameters other but differing regression types yielded higher R 2 values. The sample size of 40 was an estimate based on what is common in the field, and taking into account the aim to measure a very diverse group of volunteers. An a priori sample size calculation was not conducted due to a lack of comparable data.

Measurements were taken from 40 healthy participants (19 women and 21 men) with an average age of 43.90 (SD 17.30, range 18-87) years. Participant characteristics are summarized in Table 1 . Data were successfully recorded for all of the participants and slope levels, resulting in a complete data set ( Multimedia Appendix 1 ).

Data were normally distributed. Figure 2 visualizes the differences between the analyzed slope values on the stance phase curve. Figure 3 shows the normalized changes in the analyzed parameters with the slope of the treadmill. The analysis of variance revealed significant changes with the slope for Fmean load , Fmean unload , Fz2, Fz3, Fz4, loading and unloading slope (all P <.001). There was no significant correlation of the slope with Fmean stance ( P =.98) and Fmean mid ( P =.13). Other than the other parameters with significant changes related to slope, Fz3 had its peak at horizontal walking and values dropped when walking uphill and downhill alike. Thus, a simultaneous and short-term increase in loading slope and Fmean load combined with a decrease in Fmean unload , Fz2, Fz4, and the unloading slope indicates downhill walking, while the opposite indicates uphill walking. Fz3 is not a suitable parameter to distinguish between uphill and downhill walking, as its value decreases both when walking uphill as well as downhill. Mean values and the SD of the analyzed parameters for each treadmill slope level in absolute values are displayed in Table 2 . Table 3 indicates the linear regression slopes and R 2 -values for each of the curves shown in Figure 3 .

a Fmean stance : the mean force over the entire stance phase.

b Fmean load : the mean force between the start of the loading phase and Fz2.

c Fmean mid : the mean force between Fz2 and Fz4.

d Fmean unload : the mean force between Fz4 and the end of the unloading phase.

e Fz2: the first maximum.

f Fz3: the minimum.

g Fz4: the second maximum.

Principal Results

This study identified characteristic changes when walking with an uphill or downhill slope in insole plantar pressure data of healthy participants. The most pronounced changes with treadmill slope were found in the loading slope of the curve. A typical combination of changes in several parameters was reported that defines uphill and downhill walking and may be used for annotation and correction when analyzing such data. These changes in the trajectory of the force curve with different surface slopes relative to the force vector of Earth’s gravity are related to changes in plantar load distribution. When walking downhill, Fz2 was found to be higher compared to when walking uphill, which is caused by the more pronounced force transfer through the heel of the foot, followed by a lower second maximum due to the even lower surface at push-off.

While patient-related factors, such as curve characteristics related to body size, muscle power, degenerative disease, etc, would remain constant throughout an insole measurement, fatigue-related changes [ 15 ] may increasingly appear and then stay toward the later stages of a recording of a walking bout. Additionally, age, body height, body weight, BMI, and handgrip strength were shown to cause characteristic changes in the plantar pressure force curve, that would usually only change on a long-term scale [ 16 ]. In contrast, as shown in the present data set, walking on slopes leads to temporary and characteristic changes in specific properties of the stance-phase curve. Changes over time in the identified parameters should thus be considered and correctly interpreted when studying long-term field gait data collected via insoles. To analyze the healing process, that is, after an injury, slow changes in parameters would be expected, and a trend toward what is considered normal over several weeks [ 17 ]. Short-term changes over minutes or hours would thus not be explainable by the healing progress and should have a different cause. In addition, the asymmetry between the legs should slowly decrease throughout healing [ 18 ]. When walking on a slope, asymmetry could also be affected, if the injury causes increasing problems such as pain when walking uphill or downhill. It is also recommendable to identify the characteristics of walking with walking aids, such as crutches, to be able to classify the nature of the observed changes and the treatment stage better.

Limitations

Effects of walking speed were not analyzed in this study, even though it is known that lower extremity joint loading is affected by varying step length and cadence during graded uphill and downhill walking [ 19 ]. These parameters, however, do not seem to be necessary to successfully annotate gait data obtained by insoles. For participant or patient convenience, it would be desirable if insoles did not need to be combined with further devices or wearables. The present data suggest that at least the identification of walking on slopes does not require further sensors. It is also known that kinematic, kinetic, and electromyographic parameters differ between treadmill walking and overground gait, while spatiotemporal, kinematic, kinetic, electromyographic, and energy consumption outcome measures are largely comparable [ 20 ]. Another limitation of this study is that the parameters analyzed here can only be used when a regular gait curve is present. If this is not the case, other methods need to be applied, that is, machine learning for step detection and segmentation or the analysis of further parameters, possibly slopes and averages, or differences between individual sensors [ 21 ]. Differences between the 16 sensors embedded in each insole were not analyzed in this study and could be assessed in the future, for example, to distinguish between ground types (gravel, sand, etc). Another limitation is that the present characteristic changes that were assessed in healthy participants may differ for patients with gait disorders, depending on their disease or injury type. It will therefore be important to collect longitudinal data on different slopes from patients with defined diseases and injuries throughout the healing process or throughout different disease stages. These studies would serve to identify if the reported findings are valid also for patients, and for which patient groups this is true.

Use of Wearables in Patients

The insole technology and present data may be valuable in real-world settings when investigating changes in mechanical properties during walking, that is, in occupational health research, sport and exercise science, for urban planning, and to plan inclusive architecture. For instance, the global average slope of urban areas is about 3.70° [ 22 ]. Wearables such as pressure insoles are increasingly used to study gait and movement, as well as for fall detection, fall classification, and fall risk assessment in the daily life of patients, and furthermore for lifestyle and health monitoring [ 1 , 3 , 23 - 27 ]. Long-term monitoring, especially if combined with additional sensors, may produce large amounts of data that require advanced strategies for analyses. Apart from regression statistics, among the options is the use of machine learning algorithms trained with annotated data for pattern recognition [ 24 , 26 ]. For longer-term monitoring of patients, it would be desirable if such algorithms were trained to identify various key activities of daily life that might indicate the level of healing progress. For example, when a patient with a tibial fracture is capable of cycling again, this is likely an indication for advances in the healing process. It would also be of interest to identify risky behavior, possibly leading to excessive forces, and to warn the patient by giving, for example, an audible or haptic warning signal. To guarantee meaningful data interpretation, machine learning may be combined with conventional regression-based analyses, such as the ones proposed in this paper to best tackle data complexity. Furthermore, prediction algorithms could be implemented for falls and diseases that enable more refined individual recommendations. Ideally, such interventions would be based on live data analyses. Limitations in the computing power of small wearable devices can increasingly be mitigated by both algorithmic optimization techniques in machine learning, such as dimensionality reduction, reservoir computing, and network pruning, as well as hardware innovations [ 27 , 28 ]. In the near future, such advances will likely allow real-time feedback based on data from various sources combined [ 29 , 30 ]. Alternatively, extracting decision-making systems (symbolic artificial intelligence), such as threshold-based methods, might offer an immediate route to real-time feedback.

Sensors in Orthoses and Implants

Apart from insoles, very similar data might be collected from mechanical sensors embedded in orthoses [ 31 ] or implants [ 32 ]. Potentially, walking on a slope in these recordings changes the data in similar ways as described here. It would be highly desirable if patients did not need to use separate wearables such as insoles anymore, but if orthoses and implants had sensors embedded, not only to monitor healing progress but also to identify healing problems or complications and the need for surgical revision [ 33 ]. If similar load data could be collected by sensors in artificial hip or knee joints, or potentially even by plates or nails that stabilize bone fractures, recovery regimen could be monitored continuously and advice given on time [ 34 ]. Alarms could go off if forces exceeded certain thresholds or if live pattern analyses revealed unfavorable patterns known to be associated with exceeding forces or problems. As these developments seem to have a high potential with regard to rehabilitation and postoperative treatment, data analyses of insole data should be further studied and ideally, details such as algorithms and characteristics should be published to enable for the further development and widespread application of the named interventions.

Conclusions

Characteristic changes in the plantar-pressure stance phase curve were identified, which reflect uphill and downhill walking. Automated annotation and continuous analyses of gait data via wearables could enable improved rehabilitation and feedback systems for prevention and treatment. A combination of traditional regression statistics embedded in heuristics combined with artificial intelligence methods may yield the best results.

Acknowledgments

The Werner Siemens Foundation (project Smart Implants 2.0) funded this work. The authors would like to acknowledge the help of Aynur Gökten and Jacqueline Orth during the measurements, as well as the help of Lisa-Marie Jost in designing Figure 1 .

Authors' Contributions

CW contributed to the data processing platform, data analysis, methods, and Figure 2 . P Steinheimer conducted the measurements. BG contributed to the idea; ran the statistical analyses; interpreted the data; made the tables; and drafted, submitted, and revised this paper. TD, CS, and FC took part in the data platform implementation. EW, TD, P Slusallek, CS, FC, MO, and TP helped with data interpretation. All authors have contributed to this paper’s drafting and revision, and read and approved the submitted version of this paper.

Conflicts of Interest

TP is President and Board Member of the AO-Foundation, Switzerland, and Extended Board Member of the German Society of Orthopedic Trauma Surgery (DGU), the German Society of Orthopedic Surgery and Traumatology (DGOU), and the German Society of Surgery (DGCH). TP is also the speaker of the Medical Advisory Board of the German Ministry of Defence. The other authors do not have a conflict of interest.

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Abbreviations

Edited by G Eysenbach, T Leung; submitted 24.01.23; peer-reviewed by M Kraus, S Okita; comments to author 21.12.23; revised version received 11.01.24; accepted 17.02.24; published 08.05.24.

©Christian Wolff, Patrick Steinheimer, Elke Warmerdam, Tim Dahmen, Philipp Slusallek, Christian Schlinkmann, Fei Chen, Marcel Orth, Tim Pohlemann, Bergita Ganse. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 08.05.2024.

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

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